Peter Stone's Selected Publications
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Classified by Topic •
Classified by Publication Type •
Sorted by Date •
Sorted by First Author Last Name •
Classified by Funding Source •
Classified by Topic
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Artificial Intelligence
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Autonomic Computing
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Autonomous Traffic Management
•
Computational Epidemiology
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Game Theory
•
General Game Playing
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Machine Learning
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Machine Learning: Layered Learning
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Machine Learning: Markov Decision Processes
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Machine Learning: NeuroEvolution
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Machine Learning: Predictive State Representations
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Machine Learning: Reinforcement Learning
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Machine Learning: Transfer Learning
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Machine Learning: Imitation Learning
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Machine Learning: Learning from Humans
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Machine Learning: Lifelong Learning
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Multi-Robot Systems
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Multiagent Systems
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Multiagent Systems: Ad Hoc Teamwork
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Multiagent Systems: Agent Modeling
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Multiagent Systems: Social Agents
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Planning
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Robotics
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Robotics: Autonomous Driving
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Robotics: Quadruped Robots
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Robotics: Humanoid Robots
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Robotics: Real Robot Soccer
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Robotics: RoboCup
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Robotics: Simulated Robot Soccer
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Robotics: Vision
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Robotics: Service Robots
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Robotics: Human-Robot Interaction
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Trading Agents
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Trading Agents: Auctions
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Trading Agents: Mechanism Design
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Trading Agents: Supply Chain Management
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Unspecified
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Artificial Intelligence
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
Details
BibTeX
Download:
[pdf]
(4.3MB
)
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
W. Bradley
Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
Stone, and Scott Niekum.
In The 38th Annual AAAI Conference on Artificial
Intelligence (AAAI), February 2024.
Details
BibTeX
Download:
[pdf]
(3.6MB
)
[slides.pdf]
(3.9MB
)
[poster.pdf]
(2.9MB
)
- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
Arrasy
Rahman, Jiaxun Cui, and Peter Stone.
In
AAAI, February 2024.
the conference presentation
Details
BibTeX
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[pdf]
(1.3MB
)
[slides.ppt]
(9.2MB
)
[poster.pdf]
(956.2kB
)
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
Details
BibTeX
Download:
[pdf]
(2.0MB
)
- Dobby: A Conversational Service Robot Driven by GPT-4.
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
Hart.
In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
Details
BibTeX
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[pdf]
(863.8kB
)
[poster.pdf]
(892.0kB
)
- A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo.
Miguel Vasco, Takuma
Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, and Peter
Stone.
In Reinforcement Learning Conference (RLC), August 2024.
arXiv
version
Details
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[pdf]
(15.4MB
)
- N-Agent Ad Hoc Teamwork.
Caroline Wang, Arrasy
Rahman, Ishan Durugkar, Elad
Liebman, and Peter Stone.
In Conference on Neural Information Processing
Systems (NeurIPS), December 2024.
Details
BibTeX
Download:
[pdf]
(1.6MB
)
[slides.pdf]
(1.3MB
)
[poster.pdf]
(1.7MB
)
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
Zizhao
Wang, Caroline Wang, Xuesu
Xiao, Yuke Zhu, and Peter Stone.
In
AAAI Conference on Artificial Intelligence, February 2024.
Details
BibTeX
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[pdf]
(4.5MB
)
- Real-time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing.
Catherine Weaver, Roberto
Capobianco, Peter Wurman, Peter Stone,
and Masayoshi Tomizuka.
In American Control Conference (ACC), July 2024.
Project
page with video.
Details
BibTeX
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[pdf]
(1.5MB
)
- LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning.
Zifan Xu, Haozhu
Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, and Yanjun Qi.
In Findings
of Empirical Methods in Natural Language Processing, November 2024.
Details
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[pdf]
(1.6MB
)
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
William Yue,
Bo Liu, and Peter Stone.
In
Conference on Lifelong Learning Agents (CoLLAs), July 2024.
Details
BibTeX
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[pdf]
(599.7kB
)
[poster.pdf]
(709.1kB
)
- Models of human preference for learning reward functions.
W. Bradley Knox,
Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
Stone, and Alessandro Allievi.
Transactions on Machine Learning Research (TMLR), 2023.
Details
BibTeX
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[pdf]
(6.7MB
)
[slides.pdf]
(13.4MB
)
- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
Bo
Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
Zhu, and Peter Stone.
In 37th Conference on Neural Information Processing
Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
Details
BibTeX
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[pdf]
(37.6MB
)
[poster.pdf]
(2.6MB
)
- Improving Artificial Intelligence with Games.
Peter R. Wurman, Peter
Stone, and Michael Spranger.
Science, 381:147–8, July 2023.
Available from Science
website.
Details
BibTeX
Download:
(unavailable)
- Learning a robust multiagent driving policy for traffic congestion reduction.
Yulin
Zhang, William Macke, Jiaxun Cui,
Sharon Hornstein, Daniel Urieli, and Peter
Stone.
Neural Computing and Applications, 2023.
Details
BibTeX
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[pdf]
(1.2MB
)
- A Broader, More Inclusive Definition of AI.
Peter Stone.
Journal
of Artificial General Intelligence, 11(2):63–65, 2020.
Details
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[pdf]
(50.6kB
)
Autonomic Computing
- Autonomous Return on Investment Analysis of Additional Processing Resources.
Jonathan
Wildstrom, Peter Stone, and Emmett
Witchel.
International Journal on Autonomic Computing, 1(3):280–296, Inderscience Publishers, Inderscience
Publishers, Geneva, SWITZERLAND, 2010.
IJAC
Details
BibTeX
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(unavailable)
- Machine Learning for On-Line Hardware Reconfiguration.
Jonathan
Wildstrom, Peter Stone, Emmett
Witchel, and Mike Dahlin.
In The 20th International Joint Conference
on Artificial Intelligence, pp. 1113–1118, January 2007.
IJCAI-07
Details
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[pdf]
(98.6kB
)
[ps]
(191.7kB
)
- Adapting to Workload Changes Through On-The-Fly Reconfiguration.
Jonathan
Wildstrom, Peter Stone, Emmett
Witchel, and Mike Dahlin.
Technical Report UT-AI-TR-06-330, The University
of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2006.
At ftp://ftp.cs.utexas.edu/pub/AI-Lab/tech-reports/UT-AI-TR-06-330.pdf
Details
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(unavailable)
- Towards Self-Configuring Hardware for Distributed Computer Systems.
Jonathan
Wildstrom, Peter Stone, Emmett
Witchel, Raymond J. Mooney, and Mike
Dahlin.
In The Second International Conference on Autonomic Computing, pp. 241–249, June 2005.
ICAC-05
A revised version of the paper appeared on IBM's Developer
Works website
Details
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[pdf]
(74.0kB
)
[ps]
(104.6kB
)
- Adaptive Job Routing and Scheduling.
Shimon Whiteson
and Peter Stone.
Engineering Applications of Artificial Intelligence,
17(7):855–69, October 2004. Special issue on Autonomic Computing and Automation
Available from the publisher's
webpage
The version from this page corrects a minor error in the published version.
An earlier version appeared
in the proceedings of The Sixteenth Innovative Applications of Artificial
Intelligence Conference (IAAI 2004)
Details
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[pdf]
(664.7kB
)
[ps]
(1.1MB
)
Autonomous Traffic Management
- Learning a Robust Multiagent Driving Policy for Traffic Congestion Reduction.
Yulin
Zhang, William Macke, Jiaxun Cui,
Daniel Urieli, and Peter Stone.
In
Proceedings of the Adaptive and Learning Agents Workshop (ALA), May 2022.
Video
presentation
Details
BibTeX
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[pdf]
(573.9kB
)
[slides.pdf]
(1.4MB
)
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
Jiaxun
Cui, William Macke, Harel
Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
Stone.
In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
May 2021.
Project page, with videos
Details
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[pdf]
(1.4MB
)
[slides.pptx]
(1.5MB
)
- Selecting Compliant Agents for Opt-in Micro-Tolling.
Josiah Hanna,
Guni Sharon, Stephen
Boyles, and Peter Stone.
In Proceedings of the 33rd AAAI Conference
on Artificial Intelligence (AAAI), January 2019.
Details
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[pdf]
(2.2MB
)
- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
Guni
Sharon, Stephen D. Boyles, Shani
Alkoby, and Peter Stone.
In Proceedings of the 18th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
Details
BibTeX
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[pdf]
(1.7MB
)
[slides.pptx]
(6.5MB
)
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
Haipeng
Chen, Bo An, Guni Sharon, Josiah
P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
In Proceedings
of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
Details
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[pdf]
(2.4MB
)
[ps]
(5.9MB
)
- Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas ---
Final Report.
Kara Kockelman, Stephen Boyles, Purser
Sturgeon, Christian Claudel, Lisa Loftus-Otway, Wendy Wagner, Duncan Stewart, Guni
Sharon, Michael Albert, Peter
Stone, Josiah Hanna, Yantao Huang, Krishna Murthy Gurumurthy, Dongxu
He, Abduallah Mohamed, Rahul Patel, Tian Lei, Michele Simoni, and Sadegh Yarmohammadisatri.
Technical Report 0-6838-3,
The University of Texas at Austin Center for Transportation Research, 2018.
Available
online
Details
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(unavailable)
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
Tarun
Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
and Peter Stone.
Transportation Research Part B: Methodological,
110:104–21, 2018.
Official version from Publisher's
Webpage
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[pdf]
(1.6MB
)
- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
Guni
Sharon, Michael Albert, Tarun
Rambha, Stephen Boyles, and Peter
Stone.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
Details
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[pdf]
(1002.7kB
)
[ps]
(5.2MB
)
[slides.pptx]
(11.1MB
)
- An Assessment of Autonomous Vehicles: Traffic Impacts and Infrastructure Needs --- Final Report.
Kara Kockelman,
Stephen Boyles, Peter
Stone, Dan Fagnant, Rahul Patel, Michael W.
Levin, Guni Sharon, Michele Simoni, Michael
Albert, Hagen Fritz, Rebecca Hutchinson, Prateek Bansal, Gelb Domnenko, Pavle Bujanovic, Bumsik Kim, Elaham Pourrahmani,
Sudesh Agrawal, Tianxin Li, Josiah Hanna, Aqshems Nichols, and Jia Li.
Technical
Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, 2017.
Available
online
Details
BibTeX
Download:
(unavailable)
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
Guni
Sharon, Michael W. Levin, Josiah
P. Hanna, Tarun Rambha, Stephen
D. Boyles, and Peter Stone.
Transportation Research Part C, 84:142–157,
September 2017.
Transportation Research Part C.
Audio slides.
Contains material
that was previously published in an AAMAS-17 paper.
Details
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[pdf]
(2.8MB
)
[ps]
(4.2MB
)
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
Guni
Sharon and Peter Stone.
In Gita Sukthankar and Juan
A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
Details
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[pdf]
(1.1MB
)
[ps]
(7.1MB
)
[slides.pptx]
(140.9MB
)
- Autonomous Intersection Management for Semi-Autonomous Vehicles.
Tsz-Chiu
Au, Shun Zhang, and Peter
Stone.
In Dusan Teodorovi'c, editors, Handbook of Transportation, pp. 88–104, Routledge, 2016.
Details
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[pdf]
(2.6MB
)
- Minimum Cost Matching for Autonomous Carsharing.
Josiah P. Hanna,
Michael Albert, Donna
Chen, and Peter Stone.
In Proceedings of the 9th IFAC Symposium on
Intelligent Autonomous Vehicles (IAV 2016), June 2016.
Details
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[pdf]
(117.5kB
)
[ps]
(355.2kB
)
[slides.pdf]
(4.7MB
)
- Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas ---
Final Report.
Kara Kockelman, Stephen Boyles, Paul
Avery, Christian Claudel, Lisa Loftus-Otway, Daniel Fagnant, Prateek Bansal, Michael
Levin, Yong Zhao, Jun Liu, Lewis Clements, Wendy Wagner, Duncan Stewart, Guni
Sharon, Michael Albert, Peter
Stone, Josiah Hanna, Rahul Patel, Hagen Fritz, Tejas Choudhary, Tianxin
Li, Aqshems Nichols, Kapil Sharma, and Michele Simoni.
Technical Report 0-6838-2, The University of Texas at Austin Center
for Transportation Research, 2016.
Available online
Details
BibTeX
Download:
(unavailable)
- Auction-based autonomous intersection management.
Dustin Carlino,
Stephen D. Boyles, and Peter
Stone.
In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), October 2013.
Details
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[pdf]
(318.1kB
)
[ps]
(1.4MB
)
- Evasion Planning for Autonomous Vehicles at Intersections.
Tsz-Chiu Au,
Chien-Liang Fok, Sriram
Vishwanath, Christine Julien, and Peter
Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2012.
Details
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[pdf]
(1.3MB
)
[ps]
(18.7MB
)
- Setpoint Scheduling for Autonomous Vehicle Controllers.
Tsz-Chiu Au,
Michael Quinlan, and Peter
Stone.
In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
Details
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[pdf]
(684.9kB
)
[ps]
(2.7MB
)
- Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles.
Dustin Carlino, Mike
Depinet, Piyush Khandelwal, and Peter
Stone.
In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.
Details
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[pdf]
(727.1kB
)
[ps]
(14.3MB
)
- Automated Intersection Control: Performance of a Future Innovation Versus Current Traffic Signal Control.
David
Fajardo, Tsz-Chiu Au, Travis Waller,
Peter Stone, and David Yang.
Transportation
Research Record (TRR), 2259:223–32, 2012.
Details
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[pdf]
(591.8kB
)
- A Platform for Evaluating Autonomous Intersection Management Policies.
Chien-Liang
Fok, Maykel Hanna, Seth Gee, Tsz-Chiu
Au, Peter Stone, Christine
Julien, and Sriram Vishwanath.
In Proceedings
of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.
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[pdf]
(5.7MB
)
[ps]
(61.7MB
)
- Enforcing Liveness in Autonomous Traffic Management.
Tsz-Chiu Au, Neda Shahidi, and Peter
Stone.
In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
Details
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[pdf]
(1.1MB
)
[ps]
(31.7MB
)
- Dynamic Lane Reversal in Traffic Management.
Matthew Hausknecht,
Tsz-Chiu Au, Peter Stone, David
Fajardo, and Travis Waller.
In Proceedings of IEEE Intelligent Transportation
Systems Conference (ITSC), 2011.
Details
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[pdf]
(127.0kB
)
[ps]
(4.3MB
)
- Autonomous Intersection Management: Multi-Intersection Optimization.
Matthew
Hausknecht, Tsz-Chiu Au, and Peter
Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
2011.
Details
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[pdf]
(252.7kB
)
[ps]
(1.9MB
)
- Motion Planning Algorithms for Autonomous Intersection Management.
Tsz-Chiu
Au and Peter Stone.
In AAAI 2010 Workshop on Bridging The Gap Between
Task And Motion Planning (BTAMP), 2010.
Details
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[pdf]
(417.4kB
)
[ps]
(2.0MB
)
- Multi-Agent Social Simulation.
Itsuki Noda, Peter
Stone, Tomohisa Yamashita, and Koichi Kurumatani.
In Nakashima, H., Aghajan, H., \& Augusto, J. C., editors, Handbook
of Ambient Intelligence and Smart Environments, pp. 703–729, Springer Verlag, 2010.
Official version from
publisher's webage
Details
BibTeX
Download:
(unavailable)
- Bringing Simulation to Life: A Mixed Reality Autonomous Intersection.
Michael
Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter
Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
2010.
Video available at http://www.cs.utexas.edu/~aim/video/MixedReality.wmv
Details
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[pdf]
(1.3MB
)
[ps]
(10.6MB
)
- A Multiagent Approach to Autonomous Intersection Management.
Kurt
Dresner and Peter Stone.
Journal of Artificial Intelligence Research,
31:591–656, March 2008.
Available from journal's
web page.
Further details and videos are on the project page.
Details
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[pdf]
(1.3MB
)
[ps]
(2.2MB
)
- Mitigating Catastrophic Failure at Intersections of Autonomous Vehicles.
Kurt
Dresner and Peter Stone.
In AAMAS Workshop on Agents in Traffic and
Transportation, pp. 78–85, Estoril, Portugal, May 2008.
Details
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[pdf]
(836.3kB
)
[ps]
(1.3MB
)
- Replacing the Stop Sign: Unmanaged Intersection Control for Autonomous Vehicles.
Mark
VanMiddlesworth, Kurt Dresner, and Peter
Stone.
In AAMAS Workshop on Agents in Traffic and Transportation, pp. 94–101, Estoril, Portugal, May 2008.
Details
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[pdf]
(161.4kB
)
[ps]
(305.1kB
)
- Sharing the Road: Autonomous Vehicles meet Human Drivers.
Kurt
Dresner and Peter Stone.
In The 20th International Joint Conference
on Artificial Intelligence, pp. 1263–68, January 2007.
IJCAI-07
Details
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[pdf]
(189.9kB
)
[ps]
(287.7kB
)
- Learning Policy Selection for Autonomous Intersection Management.
Kurt
Dresner and Peter Stone.
In AAMAS 2007 Workshop on Adaptive and Learning
Agents, pp. 34–39, Honolulu, Hawaii, USA, May 2007.
Details
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[pdf]
(79.9kB
)
[ps]
(197.6kB
)
- Multiagent Traffic Management: Opportunities for Multiagent Learning.
Kurt
Dresner and Peter Stone.
In K. Tuyls et al., editors, LAMAS
2005, Lecture Notes in Artificial Intelligence, pp. 129–138, Springer Verlag, Berlin, 2006.
LAMAS-05.
Official version from Publisher's Webpage© Springer-Verlag
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[pdf]
(81.4kB
)
[ps]
(168.2kB
)
- Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management.
Kurt
Dresner and Peter Stone.
In AAMAS 2006 Workshop on Agents in Traffic
and Transportation, May 2006.
ATT 2006.
The project page with videos from the paper.
Details
BibTeX
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[pdf]
(227.5kB
)
[ps]
(376.8kB
)
- Multiagent Traffic Management: An Improved Intersection Control Mechanism.
Kurt
Dresner and Peter Stone.
In The Fourth International Joint Conference
on Autonomous Agents and Multiagent Systems, ACM Press, New York, NY, July 2005.
Some videos
referenced in the paper. The main project page
Extended
version citable as University of Texas at Austin AI lab technical
report number UT-AI-TR-04-315
AAMAS-2005
Details
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[pdf]
(143.5kB
)
[ps]
(216.7kB
)
- Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism.
Kurt
Dresner and Peter Stone.
In The Third International Joint Conference
on Autonomous Agents and Multiagent Systems, pp. 530–537, July 2004.
Some simulations
of cars driving through intersections referenced in the paper. The main project
page
AAMAS-2004
Details
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[pdf]
(233.8kB
)
[ps]
(492.0kB
)
Computational Epidemiology
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
Roberto Capobianco, Varun Kompella, James
Ault, Guni Sharon, Stacy
Jong, Spencer Fox, Lauren
Meyers, Peter R. Wurman, and Peter
Stone.
The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
Contains
material that was previously published in an AAMAS
2021 paper and a AAAI 2020 Fall
Symposium paper.
Article available from JAIR website.
Simulator
source code.
Details
BibTeX
Download:
[pdf]
(1.6MB
)
Game Theory
- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
Arrasy
Rahman, Jiaxun Cui, and Peter Stone.
In
AAAI, February 2024.
the conference presentation
Details
BibTeX
Download:
[pdf]
(1.3MB
)
[slides.ppt]
(9.2MB
)
[poster.pdf]
(956.2kB
)
- MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection.
Jiaxun
Cui, Xiaomeng Yang, Mulong Luo, Geunbae
Lee, Peter Stone, Hsien-Hsin
S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, and
Yuandong Tian.
In The Eleventh International Conference on Learning
Representations (ICLR), May 2023.
Video presentation
Details
BibTeX
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[pdf]
(769.8kB
)
[slides.pdf]
(2.1MB
)
[poster.pdf]
(1.8MB
)
- Program Embeddings for Rapid Mechanism Evaluation.
Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
and Peter Stone.
In ICRA Workshop on Multi-Robot Learning, May 2023.
Details
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[pdf]
(1.3MB
)
[poster.pdf]
(916.2kB
)
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
Harel
Yedidsion, Shani Alkoby, and Peter
Stone.
Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
arXiv
Details
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[pdf]
(478.9kB
)
- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
Guni
Sharon, Stephen D. Boyles, Shani
Alkoby, and Peter Stone.
In Proceedings of the 18th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
Details
BibTeX
Download:
[pdf]
(1.7MB
)
[slides.pptx]
(6.5MB
)
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
Haipeng
Chen, Bo An, Guni Sharon, Josiah
P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
In Proceedings
of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
Details
BibTeX
Download:
[pdf]
(2.4MB
)
[ps]
(5.9MB
)
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
Tarun
Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
and Peter Stone.
Transportation Research Part B: Methodological,
110:104–21, 2018.
Official version from Publisher's
Webpage
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- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
Guni
Sharon, Michael Albert, Tarun
Rambha, Stephen Boyles, and Peter
Stone.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
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(5.2MB
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[slides.pptx]
(11.1MB
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- Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?.
Michael
Albert, Vincent Conitzer, and Peter Stone.
In Proceedings of the
16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
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(348.6kB
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[slides.pdf]
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- Automated Design of Robust Mechanisms.
Michael Albert, Vincent
Conitzer, and Peter Stone.
In Proceedings of the Thirty-First AAAI Conference
on Artificial Intelligence (AAAI-17), Feb 2017.
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(366.4kB
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- Network-wide Adaptive Tolling for Connected and Automated vehicles.
Guni
Sharon, Michael W. Levin, Josiah
P. Hanna, Tarun Rambha, Stephen
D. Boyles, and Peter Stone.
Transportation Research Part C, 84:142–157,
September 2017.
Transportation Research Part C.
Audio slides.
Contains material
that was previously published in an AAMAS-17 paper.
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(4.2MB
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- Modeling Uncertainty in Leading Ad Hoc Teams.
Noa Agmon, Samuel
Barrett, and Peter Stone.
In Proc. of 13th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2014.
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- Leading a Best-Response Teammate in an Ad Hoc Team.
Peter Stone,
Gal A. Kaminka, and Jeffrey S. Rosenschein.
In
Esther David, Enrico Gerding, David Sarne, and Onn
Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
pp. 132–146, Springer Verlag, November 2010.
Official version from publisher's
webpage
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(179.3kB
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[ps]
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- Online Multiagent Learning against Memory Bounded Adversaries.
Doran
Chakraborty and Peter Stone.
In Machine Learning and Knowledge Discovery
in Databases, pp. 211–26, September 2008.
Official version from Publisher's
Webpage© Springer-Verlag
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[ps]
(669.2kB
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- A Polynomial-time Nash Equilibrium Algorithm for Repeated Games.
Michael
L. Littman and Peter Stone.
Decision Support Systems, 39:55–66
, 2005.
An earlier version appeared in the proceedings of the
fourth annual ACM Conference on Electronic Commerce
Official version from Decision
Support Systems
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(244.7kB
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[ps]
(272.4kB
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- Implicit Negotiation in Repeated Games.
Michael L. Littman and Peter
Stone.
In Proceedings of The Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001),
pp. 393–404, August 2001.
ATAL-2001
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(181.2kB
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General Game Playing
- The Impact of Determinism on Learning Atari 2600 Games.
Matthew Hausknecht
and Peter Stone.
In AAAI Workshop on Learning for General Competency
in Video Games, January 2015.
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- Deep Recurrent Q-Learning for Partially Observable MDPs.
Matthew Hausknecht
and Peter Stone.
In AAAI Fall Symposium on Sequential Decision Making
for Intelligent Agents (AAAI-SDMIA15), November 2015.
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(1.5MB
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[slides.pdf]
(3.8MB
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- A Neuroevolution Approach to General Atari Game Playing.
Matthew Hausknecht,
Joel Lehman, Risto Miikkulainen, and Peter Stone.
IEEE Transactions on Computational Intelligence and AI in Games,
2014.
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[pdf]
(1.3MB
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[ps]
(3.1MB
)
- General Game Learning using Knowledge Transfer.
Bikramjit Banerjee
and Peter Stone.
In The 20th International Joint Conference on Artificial
Intelligence, pp. 672–677, January 2007.
IJCAI-07
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[pdf]
(118.1kB
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[ps]
(198.5kB
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- Graph-Based Domain Mapping for Transfer Learning in General Games.
Gregory
Kuhlmann and Peter Stone.
In Proceedings of The Eighteenth European
Conference on Machine Learning, September 2007.
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[pdf]
(377.0kB
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[ps]
(601.6kB
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- Value Function Transfer for General Game Playing.
Bikramjit Banerjee,
Gregory Kuhlmann, and Peter
Stone.
In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
ICML
2006 workshop on Structural Knowledge Transfer for Machine Learning
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(172.9kB
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[ps]
(464.0kB
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- Automatic Heuristic Construction in a Complete General Game Player.
Gregory
Kuhlmann, Kurt Dresner, and Peter
Stone.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1457–62,
July 2006.
AAAI 2006
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(124.1kB
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Machine Learning
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
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- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
Arrasy
Rahman, Jiaxun Cui, and Peter Stone.
In
AAAI, February 2024.
the conference presentation
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(1.3MB
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[slides.ppt]
(9.2MB
)
[poster.pdf]
(956.2kB
)
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
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- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
Zizhao
Wang, Caroline Wang, Xuesu
Xiao, Yuke Zhu, and Peter Stone.
In
AAAI Conference on Artificial Intelligence, February 2024.
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- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
William Yue,
Bo Liu, and Peter Stone.
In
Conference on Lifelong Learning Agents (CoLLAs), July 2024.
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(599.7kB
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[poster.pdf]
(709.1kB
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- VaryNote: A Method to Automatically Vary the Number of Notes in Symbolic Music.
Juan M. Huerta, Bo
Liu, and Peter Stone.
In The 16th International Symposium on Computer
Music Multidisciplinary Research, (CMMR), Springer, November 2023.
the
conference presentation
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[pdf]
(1.4MB
)
[slides.pdf]
(2.3MB
)
- Models of human preference for learning reward functions.
W. Bradley Knox,
Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
Stone, and Alessandro Allievi.
Transactions on Machine Learning Research (TMLR), 2023.
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[pdf]
(6.7MB
)
[slides.pdf]
(13.4MB
)
- FAMO: Fast Adaptive Multitask Optimization.
Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
In Neural Information Processing Systems Foundation,
July 2023.
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- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
Bo
Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
Zhu, and Peter Stone.
In 37th Conference on Neural Information Processing
Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
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(37.6MB
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[poster.pdf]
(2.6MB
)
- Composing Efficient, Robust Tests for Policy Selection.
Dustin Morrill, Thomas J. Walsh, Daniel Hernandez,
Peter R. Wurman, and Peter Stone.
In
The 39th Conference on Uncertainty in Artificial Intelligence (UAI), August 2023.
short
video presentation, poster
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(5.5MB
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- Walking and falling: Using robot simulations to model the role of errors in infant walking.
Ossmy, Ori, Han, Danyang,
MacAlpine, Patrick, Hoch, Justine, Stone, Peter, and Adolph, Karen E..
Developmental Science, 27:e13449, September
2023.
Available from the publisher's webpage
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(unavailable)
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
Jinsoo Park, Xuesu
Xiao, Garrett Warnell, Harel
Yedidsion, and Peter Stone.
In Proceedings of the 2023 IEEE International
Conference on Robotics and Automation (ICRA 2023), May 2023.
6-minute video
presentation
Details
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[pdf]
(4.6MB
)
[slides.pptx]
(21.3MB
)
[poster.pdf]
(1.1MB
)
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
Xiaohan Zhang, Saeid Amiri,
Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
Autonomous
Robots, March 2023.
Official version
on publisher's website
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[pdf]
(2.6MB
)
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
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(4.2MB
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- Effective Mutation Rate Adaptation through Group Elite Selection.
Akarsh Kumar, Bo
Liu, Risto Miikkulainen, and Peter
Stone.
In Proceedings of the Genetic and Evolutionary Computation Conference, July 2022.
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(9.7MB
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- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
Bo
Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
In Conference
on Neural Information Processing Systems, 2022, December 2022.
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[pdf]
(4.2MB
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[slides.pdf]
(1.6MB
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[poster.pdf]
(885.6kB
)
- Dynamic Sparse Training for Deep Reinforcement Learning.
Ghada Sokar, Elena
Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy,
and Peter Stone.
In Proceedings of the 31st International Joint Conference
on Artificial Intelligence, July 2022.
arXiv version with the appendix
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[pdf]
(3.7MB
)
[slides.pptx]
(16.7MB
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- APPL: Adaptive Planner Parameter Learning.
Xuesu Xiao, Zizhao
Wang, Zifan Xu, Bo Liu, abd Gauraang
Dhamankar, Anirudh Nair, Garrett Warnell, and Peter
Stone.
Robotics and Autonomous Systems, May 2022.
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- Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
Autonomous Robots, 46:569–97,
March 2022.
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- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
Sihang Guo, Ruohan
Zhang, Bo Liu, Yifeng Zhu,
Mary Hayhoe, Dana Ballard, and Peter
Stone.
In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
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- Efficient Real-Time Inference in Temporal Convolution Networks.
Piyush
Khandelwal, James MacGlashan, Peter Wurman, and Peter
Stone.
In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
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- Conflict-Averse Gradient Descent for Multi-task learning.
Bo Liu, Xingchao
Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
In Conference on Neural
Information Processing Systems (NeurIPS), 2021, December 2021.
slides
and 9-minute presentation
github repository
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- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
Bharath Masetty, Reuth
Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
Stone.
In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
Video
presentation
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(594.9kB
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[slides.pdf]
(1.5MB
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- Learning and Reasoning for Robot Dialog and Navigation Tasks.
Keting Lu, Shiqi
Zhang, Peter Stone, and Xiaoping
Chen.
In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
Official version from ACL
Digital Library, including a link to the conference presentation
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- Reducing Sampling Error in Batch Temporal Difference Learning.
Brahma Pavse,
Ishan Durugkar, Josiah Hanna,
and Peter Stone.
In Proceedings of the 37th International Conference
on Machine Learning (ICML), July 2020.
The paper and talk is available from the ICML
2020 virtual conference page.
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(738.4kB
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[slides.pdf]
(5.2MB
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- On Sampling Error in Batch Action-Value Prediction Algorithms.
Brahma S. Pavse,
Josiah P. Hanna, Ishan Durugkar,
and Peter Stone.
In In the Offline Reinforcement Learning Workshop at
Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
5-minute
Video Presentation
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- Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks.
Lemeng Wu, Bo
Liu, Peter Stone, and Qiang Liu.
In Advances in Neural Information
Processing Systems 34 (2020), December 2020.
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[pdf]
(8.1MB
)
[slides.pdf]
(744.8kB
)
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
Felipe
Leno Da Silva, Anna Helena Reali Costa, and Peter
Stone.
In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
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- Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
Saeid Amiri, Suhua Wei, Shiqi
Zhang, Jivko Sinapov, Jesse Thomason,
and Peter Stone.
In Proceedings of the 27th International Joint Conference
on Artificial Intelligence (IJCAI-18), July 2018.
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- On the Impact of Music on Decision Making in Cooperative Tasks.
Elad
Liebman, Corey N. White, and Peter
Stone.
In 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.
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(258.5kB
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- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
Decebal Constantin Mocanu, Elena
Mocanu, Peter Stone, Phuong
H. Nguyen, Madeleine Gibescu, and Antonio
Liotta.
Nature Communications, 9(2383), June 2018.
Official version from Publisher's
Webpage.
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- Variety Wins: Soccer-Playing Robots and Infant Walking.
Ori Ossmy, Justine E. Hoch, Patrick
MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
Frontiers
in Neurorobotics, 12:19, 2018.
Available from the publisher's
webpage
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- Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions.
Jesse
Thomason, Jivko Sinapov, Raymond
J. Mooney, and Peter Stone.
In Proceedings of the 32nd Conference
on Artificial Intelligence (AAAI), February 2018.
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(1.4MB
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- Multiagent Learning Paradigms.
Karl Tuyls and Peter Stone.
In
Francesco Belardinelli and Estefania Argente, editors, Multi-Agent Systems and Agreement Technologies, Lecture Notes
in Artificial Intelligence, pp. 3–21, Springer, 2018.
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- Machine Learning Capabilities of a Simulated Cerebellum.
Matthew Hausknecht,
Wen-Ke Li, Michael Mauk, and Peter Stone.
"IEEE
Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
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- UT Austin Villa RoboCup 3D Simulation Base Code Release.
Patrick MacAlpine
and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
Code release at https://github.com/LARG/utaustinvilla3d
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(394.2kB
)
[ps]
(2.1MB
)
[slides.pdf]
(107.1MB
)
- Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines.
Kazunori
Iwata, Elad Liebman, Peter Stone,
Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii.
In Roger
Lee, editors, Computer and Information Science 2015, Studies in Computational Intelligence, Springer Verlag, Berlin,
2016.
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- Impact of Music on Decision Making in Quantitative Tasks.
Elad Liebman,
Peter Stone, and Corey
N. White.
In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
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(591.1kB
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[slides.pdf]
(678.6kB
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- Adaptation of Surrogate Tasks for Bipedal Walk Optimization.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
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(172.1kB
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[ps]
(739.5kB
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[slides.pdf]
(165.0MB
)
- When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing.
Fei
Fang, Peter Stone, and Milind
Tambe.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
Winner of Computational Sustainability Track Outstanding Paper Award at IJCAI 2015
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(456.7kB
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[ps]
(983.9kB
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[slides.pptx]
(6.2MB
)
- Representative Selection in Nonmetric Datasets.
Elad Liebman, Benny Chor, and Peter Stone.
"Applied
Artificial Intelligence", 29:807–838, 2015.
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- How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification.
Elad
Liebman, Peter Stone, and Corey
N. White.
In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
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[pdf]
(832.6kB
)
[ps]
(6.3MB
)
[slides.pdf]
(2.0MB
)
- TacTex'13: A Champion Adaptive Power Trading Agent.
Daniel Urieli
and Peter Stone.
In Proceedings of the Twenty-Eighth Conference on Artificial
Intelligence (AAAI 2014), July 2014.
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(257.8kB
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[ps]
(7.3MB
)
[slides.pdf]
(3.8MB
)
- HyperNEAT-GGP: A HyperNEAT-based Atari General Game Player.
Matthew
Hausknecht, Piyush Khandelwal, Risto
Miikkulainen, and Peter Stone.
In Genetic and Evolutionary Computation
Conference (GECCO), July 2012.
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[pdf]
(880.9kB
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[ps]
(3.3MB
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- PAC Subset Selection in Stochastic Multi-armed Bandits.
Shivaram
Kalyanakrishnan, Ambuj Tewari, Peter
Auer, and Peter Stone.
In Proceedings of the 29th International Conference
on Machine Learning (ICML), pp. 655–662, Omnipress, New York, NY, USA, June-July 2012.
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(230.2kB
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[ps]
(519.5kB
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- Using a million cell simulation of the cerebellum: Network scaling and task generality.
Wen-Ke Li, Matthew
J. Hausknecht, Peter Stone, and Michael
D. Mauk.
Neural Networks, November 2012.
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(765.8kB
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(2.5MB
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- Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker.
Matthew
Hausknecht and Peter Stone.
In Javier
Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
Video and source code available at
http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
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(324.4kB
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[ps]
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- Empowerment for continuous agent-environment systems.
Tobias Jung,
Daniel Polani, and Peter Stone.
Adaptive
Behavior, 19(1):16–39, 2011.
Available from Adaptive
Behavior page.
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[pdf]
(1.8MB
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[ps]
(1.8MB
)
- Efficient Selection of Multiple Bandit Arms: Theory and Practice.
Shivaram
Kalyanakrishnan and Peter Stone.
In Proceedings of the Twenty-seventh
International Conference on Machine Learning (ICML), 2010.
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[pdf]
(257.1kB
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[ps]
(679.3kB
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- Autonomous Return on Investment Analysis of Additional Processing Resources.
Jonathan
Wildstrom, Peter Stone, and Emmett
Witchel.
International Journal on Autonomic Computing, 1(3):280–296, Inderscience Publishers, Inderscience
Publishers, Geneva, SWITZERLAND, 2010.
IJAC
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(unavailable)
- Compositional Models for Reinforcement Learning.
Nicholas
K. Jong and Peter Stone.
In The European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery in Databases, September 2009.
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(173.0kB
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[ps]
(431.7kB
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- Adapting Price Predictions in TAC SCM.
David Pardoe and Peter
Stone.
In John Collins, Peyman Faratin, Simon
Parsons, Juan A. Rodriguez-Aguilar, Norman
M. Sadeh, Onn Shehory, and Elizabeth
Sklar, editors, Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis, Lecture Notes in Business
Information Processing, pp. 30–45, Springer Verlag, 2009.
Official version from publisher's
webpage
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(328.7kB
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[ps]
(524.0kB
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- Online Multiagent Learning against Memory Bounded Adversaries.
Doran
Chakraborty and Peter Stone.
In Machine Learning and Knowledge Discovery
in Databases, pp. 211–26, September 2008.
Official version from Publisher's
Webpage© Springer-Verlag
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[pdf]
(232.4kB
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[ps]
(669.2kB
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- A Neural Network-Based Approach to Robot Motion Control.
Uli Grasemann, Daniel
Stronger, and Peter Stone.
In Ubbo Visser, Fernando Ribeiro, Takeshi
Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence,
pp. 480–87, Springer Verlag, Berlin, 2008.
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- The Utility of Temporal Abstraction in Reinforcement Learning.
Nicholas
K. Jong, Todd Hester, and Peter
Stone.
In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
AAMAS-2008
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(136.4kB
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- Online Kernel Selection for Bayesian Reinforcement Learning.
Joseph
Reisinger, Peter Stone, and Risto
Miikkulainen.
In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
ICML 2008
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)
[ps]
(1.7MB
)
- Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents.
Daniel
Stronger and Peter Stone.
International Journal on Artificial Intelligence
Tools, 17(1):159–174, February 2008.
official
published version
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- Structure Based Color Learning on a Mobile Robot under Changing Illumination.
Mohan
Sridharan and Peter Stone.
Autonomous Robots, 23(3):161–182,
2007.
Official versionfrom
the Autonomous Robots publisher's webpage.
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- Planning Actions to Enable Color Learning on a Mobile Robot.
Mohan Sridharan
and Peter Stone.
International Journal of Information and Systems Sciences,
3(3):510–25, 2007.
official
published version
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- Action Selection for Illumination Invariant Color Learning.
Mohan Sridharan
and Peter Stone.
In The IEEE International Conference on Intelligent
Robots and Systems (IROS), 2007.
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- Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination.
Mohan
Sridharan and Peter Stone.
In The 20th International Joint Conference
on Artificial Intelligence, pp. 2212–2217, January 2007.
IJCAI-07
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- Multiagent learning is not the answer. It is the question.
Peter Stone.
Artificial
Intelligence, 171:402–05, May 2007.
Response to Shoham, Powers, and Grenager If Multi-Agent Systems is
the Answer, What is the Question?, available from Shoham's webpage.
Official version from the AIJ
publisher's webpage.
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- Learning and Multiagent Reasoning for Autonomous Agents.
Peter Stone.
In
The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
IJCAI-07
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- Machine Learning for On-Line Hardware Reconfiguration.
Jonathan
Wildstrom, Peter Stone, Emmett
Witchel, and Mike Dahlin.
In The 20th International Joint Conference
on Artificial Intelligence, pp. 1113–1118, January 2007.
IJCAI-07
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- Multiagent Traffic Management: Opportunities for Multiagent Learning.
Kurt
Dresner and Peter Stone.
In K. Tuyls et al., editors, LAMAS
2005, Lecture Notes in Artificial Intelligence, pp. 129–138, Springer Verlag, Berlin, 2006.
LAMAS-05.
Official version from Publisher's Webpage© Springer-Verlag
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- Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data.
Mohan
Sridharan and Peter Stone.
In The Ninth International Conference
on Control, Automation, Robotics and Vision, December 2006.
ICARCV
2006
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- Adapting to Workload Changes Through On-The-Fly Reconfiguration.
Jonathan
Wildstrom, Peter Stone, Emmett
Witchel, and Mike Dahlin.
Technical Report UT-AI-TR-06-330, The University
of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2006.
At ftp://ftp.cs.utexas.edu/pub/AI-Lab/tech-reports/UT-AI-TR-06-330.pdf
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- Towards Illumination Invariance in the Legged League.
Mohan Sridharan
and Peter Stone.
In Daniele
Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
in Artificial Intelligence, pp. 196–208, Springer Verlag, Berlin, 2005.
Some videos
of robots referenced in the paper.
Official version from Publisher's
Webpage© Springer-Verlag
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- Autonomous Color Learning on a Mobile Robot.
Mohan Sridharan and Peter Stone.
In Proceedings of the Twentieth National Conference on Artificial
Intelligence, July 2005.
Some videos of
the robot referenced in the paper.
AAAI 2005
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- Real-Time Vision on a Mobile Robot Platform.
Mohan Sridharan and Peter Stone.
In IEEE/RSJ International Conference on Intelligent Robots
and Systems (IROS), August 2005.
Some videos
of the robot referenced in the paper.
IROS-2005
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- Towards Self-Configuring Hardware for Distributed Computer Systems.
Jonathan
Wildstrom, Peter Stone, Emmett
Witchel, Raymond J. Mooney, and Mike
Dahlin.
In The Second International Conference on Autonomic Computing, pp. 241–249, June 2005.
ICAC-05
A revised version of the paper appeared on IBM's Developer
Works website
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- Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions.
Peter
Stone, Robert E. Schapire, Michael
L. Littman, János A. Csirik, and David
McAllester.
Journal of Artificial Intelligence Research, 19:209–242, 2003.
Available from journal's
web page.
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- Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation.
Robert
E. Schapire, Peter Stone, David
McAllester, Michael L. Littman, and János
A. Csirik.
In Proceedings of the Nineteenth International Conference on Machine Learning, 2002.
ICML-2002
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- ATTac-2000: An Adaptive Autonomous Bidding Agent.
Peter Stone, Michael L. Littman, Satinder Singh,
and Michael Kearns.
Journal of Artificial Intelligence Research,
15:189–206, June 2001.
Available from journal's web page.
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- Multiagent Systems: A survey from a machine learning perspective.
Peter
Stone and Manuela Veloso.
Autonomous Robots, 8(3):345–383, July
2000.
Formerly citable as Carnegie Mellon University CS technical report number CMU-CS-97-193. December,
1997.
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- Using Decision Tree Confidence Factors for Multiagent Control.
Peter
Stone and Manuela Veloso.
In Hiroaki
Kitano, editors, RoboCup-97: Robot Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 99–111,
Springer Verlag, Berlin, 1998.
HTML
version.
Official version from Publisher's Webpage© Springer-Verlag
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- Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function.
Peter
Stone and Manuela Veloso.
In Advances in Neural Information Processing
Systems 8, pp. 896–902, MIT Press, Cambridge, MA, 1996.
NIPS-95
HTML version.
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Machine Learning: Layered Learning
- Overlapping Layered Learning.
Patrick MacAlpine and Peter
Stone.
Artificial Intelligence, 254:21–43, Elsevier, January 2018.
Official version from Publisher's
Webpage
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
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- A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer.
David
L. Leottau, Javier Ruiz-del-Solar, Patrick
MacAlpine, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
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- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
Patrick
MacAlpine, Mike Depinet, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
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[slides.pdf]
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- Evolving Keepaway Soccer Players through Task Decomposition.
Shimon
Whiteson, Nate Kohl, Risto Miikkulainen,
and Peter Stone.
Machine Learning, 59(1):5–30, May 2005.
Some videos of the agents before and after
learning referenced in the paper.
The publisher's official
version
An earlier version appeared in the proceedings of The Genetic
and Evolutionary Computation Conference 2003 (GECCO-2003)
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- Concurrent Layered Learning.
Shimon Whiteson and Peter Stone.
In Second International Joint Conference on Autonomous Agents
and Multiagent Systems, pp. 193–200, ACM Press, New York, NY, July 2003.
AAMAS-2003
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- Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer,
Peter
Stone.
MIT Press, 2000.
A book based on my Ph.D.
thesis
Contents, availability, and on-line appendices
ISBN: 0262194384
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- Layered Learning.
Peter Stone and Manuela
Veloso.
In Ramon López de Mántaras and Enric Plaza, editors, Machine Learning: ECML 2000 (Proceedings
of the Eleventh European Conference on Machine Learning), pp. 369–381, Springer Verlag, Barcelona,Catalonia,Spain,
May/June 2000.
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- A Layered Approach to Learning Client Behaviors in the RoboCup Soccer Server.
Peter
Stone and Manuela Veloso.
Applied Artificial Intelligence, 12:165–188,
1998.
HTML version.
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Machine Learning: Markov Decision Processes
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
W. Bradley
Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
Stone, and Scott Niekum.
In The 38th Annual AAAI Conference on Artificial
Intelligence (AAAI), February 2024.
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[slides.pdf]
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[poster.pdf]
(2.9MB
)
- Models of human preference for learning reward functions.
W. Bradley Knox,
Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
Stone, and Alessandro Allievi.
Transactions on Machine Learning Research (TMLR), 2023.
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[pdf]
(6.7MB
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[slides.pdf]
(13.4MB
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- Reducing Sampling Error in Batch Temporal Difference Learning.
Brahma Pavse,
Ishan Durugkar, Josiah Hanna,
and Peter Stone.
In Proceedings of the 37th International Conference
on Machine Learning (ICML), July 2020.
The paper and talk is available from the ICML
2020 virtual conference page.
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[slides.pdf]
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- On Sampling Error in Batch Action-Value Prediction Algorithms.
Brahma S. Pavse,
Josiah P. Hanna, Ishan Durugkar,
and Peter Stone.
In In the Offline Reinforcement Learning Workshop at
Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
5-minute
Video Presentation
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- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
Felipe
Leno Da Silva, Anna Helena Reali Costa, and Peter
Stone.
In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
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- On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search.
Piyush
Khandelwal, Elad Liebman, Scott
Niekum, and Peter Stone.
In Proceedings of The 33rd International
Conference on Machine Learning, pp. 1319–1328, June 2016.
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)
[slides.pdf]
(1.7MB
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- Deep Recurrent Q-Learning for Partially Observable MDPs.
Matthew Hausknecht
and Peter Stone.
In AAAI Fall Symposium on Sequential Decision Making
for Intelligent Agents (AAAI-SDMIA15), November 2015.
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[slides.pdf]
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- Leading the Way: An Efficient Multi-robot Guidance System.
Piyush Khandelwal,
Samuel Barrett, and Peter Stone.
In
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
Accompanying videos at
https://www.youtube.com/watch?v=os1BjHgM5ao&feature=youtu.be
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- Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
W. Bradley Knox and Peter Stone.
Artificial
Intelligence, 225(), August 2015.
Artificial
Intelligence
Contains material that was previously published in a IUI 2013 paper and a RoMan 2012 paper that was nominated as a CoTeSys Cognitive Robotics BEST PAPER AWARD FINALIST.
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- Learning Complementary Multiagent Behaviors: A Case Study.
Shivaram
Kalyanakrishnan and Peter Stone.
In Jacky Baltes, Michail G. Lagoudakis,
Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot Soccer World Cup XIII, pp. 153–165, Springer
Verlag, 2010.
BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
Some simulations
referenced in the paper.
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- State Abstraction Discovery from Irrelevant State Variables.
Nicholas
K. Jong and Peter Stone.
In Proceedings of the Nineteenth International
Joint Conference on Artificial Intelligence, pp. 752–757, August 2005.
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(102.1kB
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(249.8kB
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[slides.pdf]
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- Bayesian Models of Nonstationary Markov Decision Problems.
Nicholas
K. Jong and Peter Stone.
In IJCAI 2005 workshop on Planning
and Learning in A Priori Unknown or Dynamic Domains, August 2005.
Workshop
webpage.
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- Improving Action Selection in MDP's via Knowledge Transfer.
Alexander
A. Sherstov and Peter Stone.
In Proceedings of the Twentieth
National Conference on Artificial Intelligence, July 2005.
AAAI
2005
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Machine Learning: NeuroEvolution
- The Impact of Determinism on Learning Atari 2600 Games.
Matthew Hausknecht
and Peter Stone.
In AAAI Workshop on Learning for General Competency
in Video Games, January 2015.
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- A Neuroevolution Approach to General Atari Game Playing.
Matthew Hausknecht,
Joel Lehman, Risto Miikkulainen, and Peter Stone.
IEEE Transactions on Computational Intelligence and AI in Games,
2014.
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)
- Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning.
Matthew
Taylor, Shimon Whiteson, and Peter
Stone.
In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
BEST PAPER AWARD at GECCO 2006
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(562.2kB
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- Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning.
Shimon
Whiteson and Peter Stone.
In Proceedings of the Twenty-First National
Conference on Artificial Intelligence, pp. 518–23, July 2006.
AAAI
2006
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)
- On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains.
Shimon
Whiteson and Peter Stone.
In Proceedings of the Genetic and Evolutionary
Computation Conference, pp. 1577–84, July 2006.
GECCO 2006
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(754.2kB
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- Automatic Feature Selection via Neuroevolution.
Shimon
Whiteson, Peter Stone, Kenneth
O. Stanley, Risto Miikkulainen, and Nate
Kohl.
In Proceedings of the Genetic and Evolutionary Computation Conference, June 2005.
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)
Machine Learning: Predictive State Representations
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
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- Towards Employing PSRs in a Continuous Domain.
Nicholas
K. Jong and Peter Stone.
Technical Report UT-AI-TR-04-309, The
University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
UTAustin
AI Lab technical reports
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(unavailable)
- Learning Predictive State Representations.
Satinder Singh, Michael
L. Littman, Nicholas K. Jong, David
Pardoe, and Peter Stone.
In Proceedings of the Twentieth International
Conference on Machine Learning, August 2003.
ICML-2003
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Machine Learning: Reinforcement Learning
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
Shivin Dass, Jiaheng
Hu, Ben Abbatematteo, Peter Stone, and Roberto MartÃn-MartÃn.
In Conference
on Robot Learning (CoRL), November 2024.
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)
- Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
Jiaheng
Hu, Zizhao Wang, Roberto MartÃn-MartÃn, and Peter
Stone.
In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
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- Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration.
Borja G. Leon,
Francesco Riccio, Kaushik Subramanian, and Peter R. Wurman an Peter Stone.
In
Conference on Neural Information Processing Systems (NeurIPS), December 2024.
Project
website (with videos)
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[slides.pdf]
(1.4MB
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[poster.pdf]
(1.5MB
)
- Multistep Inverse Is Not All You Need.
Alexander Levine, Peter Stone,
and Amy Zhang.
Reinforcement Learning Conference, 2024.
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(1.8MB
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[slides.pdf]
(4.8MB
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[poster.pdf]
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- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
Arrasy
Rahman, Jiaxun Cui, and Peter Stone.
In
AAAI, February 2024.
the conference presentation
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[pdf]
(1.3MB
)
[slides.ppt]
(9.2MB
)
[poster.pdf]
(956.2kB
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- Relaxed Exploration Constrained Reinforcement Learning.
Shahaf S. Shperberg, Bo
Liu, and Peter Stone.
In Conference on Autonomous Agents and Multiagent
Systems, May 2024.
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- SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.
Zizhao
Wang, Jiaheng Hu, Caleb Chuck, Stephen
Chen, Roberto MartÃn-MartÃn, Amy Zhang, Scott Niekum, and Peter
Stone.
In Conference on Neural Information Processing Systems (NeurIPS), December 2024.
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- N-Agent Ad Hoc Teamwork.
Caroline Wang, Arrasy
Rahman, Ishan Durugkar, Elad
Liebman, and Peter Stone.
In Conference on Neural Information Processing
Systems (NeurIPS), December 2024.
Details
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[pdf]
(1.6MB
)
[slides.pdf]
(1.3MB
)
[poster.pdf]
(1.7MB
)
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
Zizhao
Wang, Caroline Wang, Xuesu
Xiao, Yuke Zhu, and Peter Stone.
In
AAAI Conference on Artificial Intelligence, February 2024.
Details
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- Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
Ziping Xu, Zifan
Xu, Runxuan Jiang, Peter Stone, and Ambuj
Tewari.
In International Conference on Learning Representations (ICLR), May 2024.
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- Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning.
Zifan
Xu, Amir Hossain Raj, Xuesu Xiao, and Peter
Stone.
In IEEE International Conference on Robotics and Automation, May 2024.
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- f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences.
Siddhant Agarwal, Ishan
Durugkar, Peter Stone, and Amy Zhang.
In Conference on Neural Information
Processing Systems, December 2023.
Details
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[pdf]
(3.4MB
)
[slides.pptx]
(13.6MB
)
[poster.pdf]
(1.8MB
)
- Task Phasing: Automated Curriculum Learning from Demonstrations.
Vaibhav Bajaj, Guni
Sharon, and Peter Stone.
In Proceedings of the 33rd International
Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
Accompanying code
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- The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications.
Serena
Booth, W Bradley Knox, Julie Shah, Scott
Niekum, Peter Stone, and Alessandro Allievi.
In Proceedings of the
37th AAAI Conference on Artificial Intelligence (AAAI), Feb 2023.
Project
page with slides and video.
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- MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection.
Jiaxun
Cui, Xiaomeng Yang, Mulong Luo, Geunbae
Lee, Peter Stone, Hsien-Hsin
S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, and
Yuandong Tian.
In The Eleventh International Conference on Learning
Representations (ICLR), May 2023.
Video presentation
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(769.8kB
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[slides.pdf]
(2.1MB
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[poster.pdf]
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- Causal Policy Gradient for Whole-Body Mobile Manipulation.
Jiaheng Hu,
Peter Stone, and Roberto Martin-Martin.
In Robotics: Science and Systems
(RSS), July 2023.
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- Models of human preference for learning reward functions.
W. Bradley Knox,
Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
Stone, and Alessandro Allievi.
Transactions on Machine Learning Research (TMLR), 2023.
Details
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[pdf]
(6.7MB
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[slides.pdf]
(13.4MB
)
- Reward (Mis)design for Autonomous Driving.
W. Bradley Knox, Alessandro Allievi,
Holger Banzhaf, Felix Schmitt, and Peter Stone.
Artificial Intelligence,
316:103829, 2023.
Paper webpage
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(696.3kB
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- Event Tables for Efficient Experience Replay.
Varun Kompella, Thomas Walsh, Samuel
Barrett, Peter Wurman, and Peter Stone.
Transactions
on Machine Learning Research (TMLR), 2023.
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- Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning.
Bo
Liu, Yihao Feng, Qiang Liu, and Peter Stone.
In Thirty-Seventh AAAI
Conference on Artificial Intelligence (AAAI), Februray 2023.
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- ELDEN: Exploration via Local Dependencies.
Zizhao Wang, Jiaheng
Hu, Peter Stone, and Roberto MartÃn-MartÃn.
In Conference on Neural
Information Processing Systems, December 2023.
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- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
Caroline
Wang, Garrett Warnell, and Peter
Stone.
In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
May 2023.
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- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
Caroline
Wang, Ishan Durugkar, Elad Liebman,
and Peter Stone.
In Proceedings of the 37th AAAI Conference on Artificial
Intelligence (AAAI-23), February 2023.
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- Model-Based Meta Automatic Curriculum Learning.
Zifan Xu, Yulin
Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian
Jiang, Bo Liu, and Peter Stone.
In
The Second Conference on Lifelong Learning Agents (CoLLAs), August 2023.
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- Learning a robust multiagent driving policy for traffic congestion reduction.
Yulin
Zhang, William Macke, Jiaxun Cui,
Sharon Hornstein, Daniel Urieli, and Peter
Stone.
Neural Computing and Applications, 2023.
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- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
Eddy Hudson, Garrett
Warnell, Faraz Torabi, and Peter
Stone.
In International Conference on Robotics and Automation (ICRA), May 2022.
Presentation
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- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
Haresh
Karnan, Garrett Warnell, Xuesu
Xiao, and Peter Stone.
In International Conference on Robotics and
Automation, 2022, May 2022.
Poster,
Video
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- Adversarial Imitation Learning from Video using a State Observer.
Haresh
Karnan, Garrett Warnell, Faraz
Torabi, and Peter Stone.
In International Conference on Robotics
and Automation, 2022, May 2022.
Video
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- Value Function Decomposition for Iterative Design of Reinforcement Learning Agents.
James MacGlashan, Evan Archer,
Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, and Peter
Stone.
In Conference on Neural Information Processing Systems (NeurIPS), December 2022.
5-minute
Video Presentation; the
slides
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- Task Factorization in Curriculum Learning.
Reuth Mirsky,
Shahaf S. Shperberg, Yulin Zhang, Zifan
Xu, Yuqian Jiang, Jiaxun Cui, and Peter
Stone.
In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.
recorded
presentation
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- Causal Dynamics Learning for Task-Independent State Abstraction.
Zizhao
Wang, Xuesu Xiao, Zifan Xu, Yuke
Zhu, and Peter Stone.
In Proceedings of the 39th International Conference
on Machine Learning (ICML2022), July 2022.
recorded presentation
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- Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning.
Peter
R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik
Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Varun
Kompella, Piyush Khandelwal, HaoChih
Lin, Patrick MacAlpine, Declan Oller, Craig Sherstan, Takuma Seno, Michael
D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead,
Peter Duerr, Peter Stone, Michael Spranger, and and
Hiroaki Kitano.
Nature, 62:223–28, Feb. 2022.
Available from Nature
website.
project webpage
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- Learning a Robust Multiagent Driving Policy for Traffic Congestion Reduction.
Yulin
Zhang, William Macke, Jiaxun Cui,
Daniel Urieli, and Peter Stone.
In
Proceedings of the Adaptive and Learning Agents Workshop (ALA), May 2022.
Video
presentation
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- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
Yunshu Du, Garrett
Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
E. Taylor.
Neural Computing and Applications, May 2021.
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- Adversarial Intrinsic Motivation for Reinforcement Learning.
Ishan Durugkar,
Mauricio Tec, Scott Niekum, and Peter
Stone.
In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
December 2021.
slides and video presentation
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- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
Keya
Ghonasgi, Reuth Mirsky, Sanmit
Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
Deshpande.
In International Conference on Intelligent Robots and Systems (IROS), September 2021.
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- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
Josiah
P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
Warnell, and Peter Stone.
Special Issue on Reinforcement Learning
for Real Life, Machine Learning, 2021, May 2021.
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- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
Josiah
P. Hanna, Scott Niekum, and Peter
Stone.
Machine Learning (MLJ), 110:1267–1317, May 2021.
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- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
Eddy Hudson, Garrett
Warnell, and Peter Stone.
In Autonomous Robots and Multirobot Systems
Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
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- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
Yuqian
Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
In
Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
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- Policy Evaluation in Continuous MDPs with Efficient Kernelized Gradient Temporal Difference.
Alec Koppel, Garrett
Warnell, Ethan Stump, Peter Stone, and Alejandro Ribeiro.
IEEE Transactions
on Automatic Control, 66(4):1856–63, April 2021.
official
online version
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- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
Bo
Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
Zhu, and Animashree Anandkumar.
In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
2021 (ICML), July 2021.
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- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
Bharath Masetty, Reuth
Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
Stone.
In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
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- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
Faraz
Torabi, Garrett Warnell, and Peter
Stone.
In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
2021.
Video presentation
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- A Scavenger Hunt for Service Robots.
Harel Yedidsion,
Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
Stone.
In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
Video presentation
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- The EMPATHIC Framework for Task Learning from Implicit Human Feedback.
Yuchen
Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott
Niekum, and W. Bradley Knox.
In Proceedings of the 4th Conference on Robot
Learning (CoRL 2020), November 2020.
5-minute video presentation;
47-minute in-depth talk.
Project website.
Raw
data from experiments.
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- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
Siddarth Desai, Ishan
Durugkar, Haresh Karnan, Garrett
Warnell, Josiah Hanna, and Peter
Stone.
In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
December 2020.
Poster
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- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Siddharth Desai, Haresh
Karnan, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
11-minute video
presentation.
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- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
Ishan
Durugkar, Elad Liebman, and Peter
Stone.
In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
2020.
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- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
Haresh
Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
14-minute video
presentation.
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- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
Sanmit
Narvekar, Bei Peng, Matteo Leonetti, Jivko
Sinapov, Matthew E. Taylor, and Peter
Stone.
Journal of Machine Learning Research, 21(181):1–50, 2020.
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- Generalizing Curricula for Reinforcement Learning.
Sanmit Narvekar
and Peter Stone.
In 4th Lifelong Learning Workshop at the International
Conference on Machine Learning (ICML 2020), July 2020.
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- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
Brahma
Pavse, Faraz Torabi, Josiah
Hanna, Garrett Warnell, and Peter
Stone.
IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
Video
of the experiments; 13-minute video presentation.
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- Reducing Sampling Error in Batch Temporal Difference Learning.
Brahma Pavse,
Ishan Durugkar, Josiah Hanna,
and Peter Stone.
In Proceedings of the 37th International Conference
on Machine Learning (ICML), July 2020.
The paper and talk is available from the ICML
2020 virtual conference page.
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- On Sampling Error in Batch Action-Value Prediction Algorithms.
Brahma S. Pavse,
Josiah P. Hanna, Ishan Durugkar,
and Peter Stone.
In In the Offline Reinforcement Learning Workshop at
Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
5-minute
Video Presentation
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- Deep R-Learning for Continual Area Sweeping.
Rishi Shah, Yuqian Jiang, Justin
Hart, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
1-minute
video demonstration; 13-minute Video
presentation.
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- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
Josiah
Hanna, Scott Niekum, and Peter
Stone.
In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
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- Reducing Sampling Error in Policy Gradient Learning.
Josiah Hanna
and Peter Stone.
In Proceedings of the 18th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
This paper contains material that was previously
presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
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- The right music at the right time: adaptive personalized playlists based on sequence modeling.
Elad
Liebman, Maytal Saar-Tsechansky, and Peter
Stone Peter Stone.
Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
and The Management Information Systems Research Center, 2019.
Available from publisher's
website.
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- Learning Curriculum Policies for Reinforcement Learning.
Sanmit Narvekar
and Peter Stone.
In Proceedings of the 18th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
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- Agents teaching agents: a survey on inter-agent transfer learning.
Felipe Leno
Da Silva, Garrett Warnell, Anna
Helena Reali Costa, and Peter Stone.
Autonomous Agents and Multi-Agent
Systems, Dec 2019.
Official version from JAAMAS
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- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
Felipe
Leno Da Silva, Anna Helena Reali Costa, and Peter
Stone.
In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
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- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
Ruohan
Zhang, Faraz Torabi, Lin Guan, Dana
H. Ballard, and Peter Stone.
In Proceedings of the 28th International
Joint Conference on Artificial Intelligence (IJCAI), August 2019.
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- Towards a Data Efficient Off-Policy Policy Gradient.
Josiah Hanna
and Peter Stone.
In AAAI Spring Symposium on Data Efficient Reinforcement
Learning, March 2018.
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- A Stitch in Time - Autonomous Model Management via Reinforcement Learning.
Elad
Liebman, Eric Zavesky, and Peter Stone.
In Proceedings of the 17th
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
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- State Abstraction Synthesis for Discrete Models of Continuous Domains.
Jacob
Menashe and Peter Stone.
In Data Efficient Reinforcement Learning
Workshop at AAAI Spring Symposium, March 2018.
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- Deterministic Implementations for Reproducibility in Deep Reinforcement Learning.
Prabhat Nagarajan, Garrett
Warnell, and Peter Stone.
In 2nd Reproducibility in Machine Learning
Workshop at ICML 2018, July 2018.
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- Learning a Policy for Opportunistic Active Learning.
Aishwarya Padmakumar, Peter
Stone, and Raymond J. Mooney.
In Proceedings of the Conference on
Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
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- Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
Garrett
Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
In Proceedings
of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
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- TD Learning with Constrained Gradients.
Ishan Durugkar and Peter
Stone.
In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
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- Data-Efficient Policy Evaluation Through Behavior Policy Search.
Josiah
Hanna, Philip Thomas, Peter Stone, and Scott
Niekum.
In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
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- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
Josiah
Hanna, Peter Stone, and Scott
Niekum.
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
May 2017.
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- Intrinsically motivated model learning for developing curious robots.
Todd
Hester and Peter Stone.
Artificial Intelligence, 247:170–86,
June 2017.
from journal website.
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- Designing Better Playlists with Monte Carlo Tree Search.
Elad Liebman,
Piyush Khandelwal, Maytal
Saar-Tsechansky, and Peter Stone.
In Proceedings of the Twenty-Ninth
Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
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- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
Sanmit
Narvekar, Jivko Sinapov, and Peter
Stone.
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
2017.
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(826.2kB
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- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
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- State Aggregation through Reasoning in Answer Set Programming.
Ginevra Gaudioso, Matteo
Leonetti, and Peter Stone.
In Proceedings of the IJCAI Workshop on
Autonomous Mobile Service Robots (WSR 16), July 2016.
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- Deep Reinforcement Learning in Parameterized Action Space.
Matthew Hausknecht
and Peter Stone.
In Proceedings of the International Conference on Learning
Representations (ICLR), May 2016.
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- Grounded Semantic Networks for Learning Shared Communication Protocols.
Matthew
Hausknecht and Peter Stone.
In Deep Reinforcement Learning, NIPS
Workshop, December 2016.
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- On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning.
Matthew
Hausknecht and Peter Stone.
In Deep Reinforcement Learning: Frontiers
and Challenges, IJCAI Workshop, July 2016.
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- Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork.
Matthew
Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan,
and Peter Stone.
In AAMAS Adaptive Learning Agents (ALA) Workshop,
May 2016.
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- Deep Imitation Learning for Parameterized Action Spaces.
Matthew Hausknecht,
Yilun Chen, and Peter
Stone.
In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
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- A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
Matteo
Leonetti, Luca Iocchi, and Peter Stone.
Artificial Intelligence,
241:103 – 130, September 2016.
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- Source Task Creation for Curriculum Learning.
Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti,
and Peter Stone.
In Proceedings of the 15th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
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- Deep Recurrent Q-Learning for Partially Observable MDPs.
Matthew Hausknecht
and Peter Stone.
In AAAI Fall Symposium on Sequential Decision Making
for Intelligent Agents (AAAI-SDMIA15), November 2015.
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- DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation.
Elad
Liebman, Maytal Saar-Tsechansky, and Peter
Stone.
In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
May 2015.
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(38.4MB
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- Monte Carlo Hierarchical Model Learning.
Jacob Menashe and Peter Stone.
In Proceedings of the 14th International Conference on Autonomous
Agents and Multiagent Systems (AAMAS), May 2015.
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- Learning Inter-Task Transferability in the Absence of Target Task Samples.
Jivko
Sinapov, Sanmit Narvekar, Matteo
Leonetti, and Peter Stone.
In Proceedings of the International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
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- Communicating with Unknown Teammates.
Samuel Barrett, Noa
Agmon, Noam Hazon, Sarit Kraus,
and Peter Stone.
In Proceedings of the Twenty-First European Conference
on Artificial Intelligence, August 2014.
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- TacTex'13: A Champion Adaptive Power Trading Agent.
Daniel Urieli
and Peter Stone.
In Proceedings of the Twenty-Eighth Conference on Artificial
Intelligence (AAAI 2014), July 2014.
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- Multiagent Learning in the Presence of Memory-Bounded Agents.
Doran
Chakraborty and Peter Stone.
Autonomous Agents and Multiagent Systems
(JAAMAS), Springer, 2013.
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- Cooperating with a Markovian Ad Hoc Teammate.
Doran
Chakraborty and Peter Stone.
In Proceedings of the 12th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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- Targeted Opponent Modeling of Memory-Bounded Agents.
Doran
Chakraborty, Noa Agmon, and Peter
Stone.
In Proceedings of the Adaptive Learning Agents Workshop (ALA), May 2013.
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- TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots.
Todd
Hester and Peter Stone.
Machine Learning, 90(3):385–429,
2013.
Official version
from journal website.
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- The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots.
Todd
Hester and Peter Stone.
In Sven Behnke, Arnoud Visser, Rong Xiong, and
Manuela Veloso, editors, RoboCup-2013: Robot Soccer World Cup XVII, Lecture
Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
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- Learning Exploration Strategies in Model-Based Reinforcement Learning.
Todd
Hester, Manuel Lopes, and Peter
Stone.
In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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(258.7kB
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[ps]
(2.4MB
)
- Training a Robot via Human Feedback: A Case Study.
W. Bradley Knox, Peter
Stone, and Cynthia Breazeal.
In International Conference on
Social Robotics, October 2013.
BEST PAPER AWARD WINNER at ICSR 2013
An
associated video summarizing the paper (direct
link).
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- Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy
System.
Daniel Urieli and Peter
Stone.
In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML'13),
Sep 2013.
Official publisher version
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[pdf]
(2.3MB
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[slides.pdf]
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- A Learning Agent for Heat-Pump Thermostat Control.
Daniel Urieli
and Peter Stone.
In Proceedings of the 12th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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(426.6kB
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- RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control.
Todd
Hester, Michael Quinlan, and Peter
Stone.
In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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- How Humans Teach Agents: A New Experimental Perspective.
W. Bradley Knox,
Brian D. Glass, Bradley
C. Love, W. Todd Maddox, and Peter
Stone.
International Journal of Social Robotics, 4:409–421, Springer Netherlands, October 2012. 10.1007/s12369-012-0163-x
International Journal of Social Robotics
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- The Nature of Belief-Directed Exploratory Choice in Human Decision-Making.
W.
Bradley Knox, A. Ross Otto, Peter
Stone, and Bradley Love.
Frontiers in Psychology, 2(398), January 2012.
Frontiers in Psychology
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article from publisher (free)
A follow-up
commentary by Erica Yu.
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- Reinforcement Learning from Simultaneous Human and MDP Reward.
W. Bradley Knox
and Peter Stone.
In Proceedings of the 11th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
AAMAS 2012
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(4.9MB
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- Learning from feedback on actions past and intended.
W. Bradley Knox,
Cynthia Breazeal, and Peter
Stone.
In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports
Session (HRI), March 2012.
HRI 2012
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- Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree.
Doran
Chakraborty and Peter Stone.
In Proceedings of the Twenty Eighth
International Conference on Machine Learning (ICML), 2011.
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(223.3kB
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- Learning and Using Models.
Todd Hester and Peter
Stone.
In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer
Verlag, Berlin, Germany, 2011.
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- Characterizing Reinforcement Learning Methods through Parameterized Learning Problems.
Shivaram
Kalyanakrishnan and Peter Stone.
Machine Learning (MLJ), 84(1--2):205–247,
July 2011.
Publisher's
on-line version
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- On Learning with Imperfect Representations.
Shivaram Kalyanakrishnan
and Peter Stone.
In Proceedings of the 2011 IEEE Symposium on Adaptive
Dynamic Programming and Reinforcement Learning, pp. 17–24, IEEE, April 2011.
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- Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report.
W. Bradley
Knox and Peter Stone.
In IJCAI 2011 Workshop on Agents Learning Interactively
from Human Teachers (ALIHT), July 2011.
IJCAI 2011 Workshop
on Agents Learning Interactively from Human Teachers (ALIHT)
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[pdf]
(372.4kB
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(41.6MB
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- An Introduction to Inter-task Transfer for Reinforcement Learning.
Matthew
E. Taylor and Peter Stone.
AI Magazine, 32(1):15–34,
2011.
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[pdf]
(237.0kB
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[ps]
(773.0kB
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- Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning.
Shimon
Whiteson, Brian Tanner, Matthew
E. Taylor, and Peter Stone.
In IEEE Symposium on Adaptive Dynamic
Programming and Reinforcement Learning (ADPRL), April 2011.
2011
IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)
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- Transfer Learning for Reinforcement Learning on a Physical Robot.
Samuel
Barrett, Matt E. Taylor, and Peter
Stone.
In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents
Workshop (AAMAS - ALA), May 2010.
AAMAS ALA 2010
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- Convergence, Targeted Optimality and Safety in Multiagent Learning.
Doran
Chakraborty and Peter Stone.
In Proceedings of the Twenty-seventh
International Conference on Machine Learning (ICML), June 2010.
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[pdf]
(196.9kB
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[ps]
(474.1kB
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- Real Time Targeted Exploration in Large Domains.
Todd Hester and Peter Stone.
In The Ninth International Conference on Development and Learning
(ICDL), August 2010.
ICDL 2010
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- Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration.
Tobias
Jung and Peter Stone.
In The European Conference on Machine Learning
(ECML), September 2010.
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[pdf]
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(6.5MB
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[slides.pdf]
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- Learning Complementary Multiagent Behaviors: A Case Study.
Shivaram
Kalyanakrishnan and Peter Stone.
In Jacky Baltes, Michail G. Lagoudakis,
Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot Soccer World Cup XIII, pp. 153–165, Springer
Verlag, 2010.
BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
Some simulations
referenced in the paper.
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[pdf]
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- Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning.
W. Bradley
Knox and Peter Stone.
In Proc. of 9th Int. Conf. on Autonomous Agents
and Multiagent Systems (AAMAS 2010), May 2010.
Winner of the Pragnesh Jay Modi BEST STUDENT PAPER AWARD (and
best paper award nominee).
The TAMER project page with videos
of TAMER in action.
AAMAS-2010
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- Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning.
Shimon Whiteson, Matthew
E. Taylor, and Peter Stone.
Journal of Autonomous Agents and
Multi-Agent Systems, 21(1):1–27, 2010.
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- A Task Specification Language for Bootstrap Learning.
Ian
Fasel, Michael Quinlan, and Peter
Stone.
In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
AAAI
Spring 2009 Symposium: Agents that Learn from Human Teachers
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- Generalized Model Learning for Reinforcement Learning in Factored Domains.
Todd
Hester and Peter Stone.
In The Eighth International Conference on
Autonomous Agents and Multiagent Systems (AAMAS), May 2009.
AAMAS
2009
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- An Empirical Comparison of Abstraction in Models of Markov Decision Processes.
Todd
Hester and Peter Stone.
In Proceedings of the ICML/UAI/COLT Workshop
on Abstraction in Reinforcement Learning, June 2009.
ICML ARL 2009
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(127.0kB
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- Feature Selection for Value Function Approximation Using Bayesian Model Selection.
Tobias
Jung and Peter Stone.
In The European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery in Databases, September 2009.
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[slides.pdf]
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- An Empirical Analysis of Value Function-Based and Policy Search Reinforcement Learning.
Shivaram
Kalyanakrishnan and Peter Stone.
In The Eighth International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), pp. 749–756, International Foundation for Autonomous Agents
and Multiagent Systems, May 2009.
AAMAS 2009
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(1.7MB
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- Interactively Shaping Agents via Human Reinforcement: The TAMER Framework.
W. Bradley
Knox and Peter Stone.
In The Fifth International Conference on Knowledge
Capture, September 2009.
The TAMER project page with
videos of TAMER in action.
K-CAP
2009
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(540.2kB
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- Design Principles for Creating Human-Shapable Agents.
W. Bradley Knox,
Ian Fasel, and Peter
Stone.
In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
AAAI
Spring 2009 Symposium: Agents that Learn from Human Teachers
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(400.8kB
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- Transfer Learning for Reinforcement Learning Domains: A Survey.
Matthew
E. Taylor and Peter Stone.
Journal of Machine Learning Research,
10(1):1633–1685, 2009.
Official version
from journal website.
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[pdf]
(399.8kB
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[ps]
(579.4kB
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- Instance-Based Action Models for Fast Action Planning.
Mazda
Ahmadi and Peter Stone.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi,
and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp.
1–16, Springer Verlag, Berlin, 2008.
BEST PAPER AWARD WINNER at RoboCup International Symposium.
Official
version from Publisher's Webpage© Springer-Verlag
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[pdf]
(466.3kB
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[ps]
(3.0MB
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- Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ.
Nicholas
K. Jong and Peter Stone.
In Proceedings of the Twenty-Fifth
International Conference on Machine Learning, July 2008.
ICML 2008
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(157.5kB
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- Model-based Reinforcement Learning in a Complex Domain.
Shivaram
Kalyanakrishnan, Peter Stone, and Yaxin
Liu.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World
Cup XI, Lecture Notes in Artificial Intelligence, pp. 171–83, Springer Verlag, Berlin, 2008.
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[pdf]
(200.9kB
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[ps]
(515.0kB
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- TAMER: Training an Agent Manually via Evaluative Reinforcement.
W. Bradley
Knox and Peter Stone.
In IEEE 7th International Conference on Development
and Learning, August 2008.
ICDL-2008
Also available in IEEE
Xplore, 9-12 Aug. 2008 Pages:292 - 297
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- Transferring Instances for Model-Based Reinforcement Learning.
Matthew E. Taylor,
Nicholas K. Jong, and Peter
Stone.
In Machine Learning and Knowledge Discovery in Databases, pp. 488–505, September 2008.
Official
version from Publisher's Webpage© Springer-Verlag
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- Autonomous Transfer for Reinforcement Learning.
Matthew E. Taylor,
Gregory Kuhlmann, and Peter
Stone.
In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
AAMAS-2008
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(233.3kB
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[ps]
(391.7kB
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- IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks.
Mazda
Ahmadi, Matthew E. Taylor, and Peter
Stone.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
BEST PAPER AWARD NOMINEE.
AAMAS-2007
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[pdf]
(261.6kB
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(1.0MB
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- The Chin Pinch: A Case Study in Skill Learning on a Legged Robot.
Peggy
Fidelman and Peter Stone.
In Gerhard Lakemeyer, Elizabeth
Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
in Artificial Intelligence, pp. 59–71, Springer Verlag, Berlin, 2007.
Some videos
referenced in the paper.
Details
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(186.9kB
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- Model-Based Function Approximation for Reinforcement Learning.
Nicholas
K. Jong and Peter Stone.
In The Sixth International Joint Conference
on Autonomous Agents and Multiagent Systems, May 2007.
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[pdf]
(321.1kB
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- Model-Based Exploration in Continuous State Spaces.
Nicholas
K. Jong and Peter Stone.
In The Seventh Symposium on Abstraction,
Reformulation, and Approximation, July 2007.
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(324.3kB
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(1.1MB
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- Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study.
Shivaram
Kalyanakrishnan, Yaxin Liu, and Peter
Stone.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
72–85, Springer Verlag, Berlin, 2007.
BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
Some simulations referenced in the paper.
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[pdf]
(992.2kB
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(1.6MB
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- Batch Reinforcement Learning in a Complex Domain.
Shivaram Kalyanakrishnan
and Peter Stone.
In The Sixth International Joint Conference on Autonomous
Agents and Multiagent Systems, pp. 650–657, ACM, New York, NY, USA, May 2007.
BEST PAPER AWARD NOMINEE.
AAMAS-2007
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[pdf]
(186.4kB
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(384.8kB
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- Graph-Based Domain Mapping for Transfer Learning in General Games.
Gregory
Kuhlmann and Peter Stone.
In Proceedings of The Eighteenth European
Conference on Machine Learning, September 2007.
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[pdf]
(377.0kB
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(601.6kB
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- Autonomous Learning of Stable Quadruped Locomotion.
Manish
Saggar, Thomas D'Silva, Nate Kohl, and Peter
Stone.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
98–109, Springer Verlag, Berlin, 2007.
BEST PAPER AWARD NOMINEE at RoboCup International Symposium.
Some videos referenced in the paper.
Details
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(1.1MB
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(26.8MB
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- Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
Matthew
E. Taylor, Peter Stone, and Yaxin
Liu.
Journal of Machine Learning Research, 8(1):2125–2167, 2007.
Available from journal's
web page.
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(499.9kB
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(831.3kB
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- Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison.
Matthew
E. Taylor, Shimon Whiteson, and Peter
Stone.
In Proceedings of the Twenty-Second Conference on Artificial Intelligence, pp. 1675–1678,
July 2007. Nectar Track
AAAI 2007
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(99.7kB
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(190.4kB
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- Cross-Domain Transfer for Reinforcement Learning.
Matthew E. Taylor
and Peter Stone.
In Proceedings of the Twenty-Fourth International
Conference on Machine Learning, June 2007.
ICML
2007
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(220.7kB
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(325.4kB
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- Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning.
Matthew
E. Taylor, Shimon Whiteson, and Peter
Stone.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
AAMAS-2007
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(222.5kB
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[ps]
(525.2kB
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- Representation Transfer for Reinforcement Learning.
Matthew E. Taylor
and Peter Stone.
In AAAI 2007 Fall Symposium on Computational
Approaches to Representation Change during Learning and Development, November 2007.
2007
AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development
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- Empirical Studies in Action Selection for Reinforcement Learning.
Shimon
Whiteson, Matthew E. Taylor, and Peter
Stone.
Adaptive Behavior, 15(1):33–50, March 2007.
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(828.6kB
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(1.5MB
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- Adaptive Tile Coding for Value Function Approximation.
Shimon
Whiteson, Matthew E. Taylor, and Peter
Stone.
Technical Report AI-TR-07-339, University of Texas at Austin, 2007.
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[pdf]
(329.4kB
)
[ps]
(942.5kB
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- Value Function Transfer for General Game Playing.
Bikramjit Banerjee,
Gregory Kuhlmann, and Peter
Stone.
In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
ICML
2006 workshop on Structural Knowledge Transfer for Machine Learning
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(172.9kB
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- Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping.
Yaxin
Liu and Peter Stone.
In Proceedings of the Twenty-First National
Conference on Artificial Intelligence, pp. 415–20, July 2006.
AAAI
2006
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(151.7kB
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- Keepaway Soccer: From Machine Learning Testbed to Benchmark.
Peter Stone,
Gregory Kuhlmann, Matthew E. Taylor,
and Yaxin Liu.
In Itsuki
Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX,
pp. 93–105, Springer Verlag, Berlin, 2006.
Some simulations
of keepaway referenced in the paper and keepaway software.
Official version from Publisher's
Webpage© Springer-Verlag
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[pdf]
(567.7kB
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(2.3MB
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- Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning.
Matthew
Taylor, Shimon Whiteson, and Peter
Stone.
In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
BEST PAPER AWARD at GECCO 2006
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(235.9kB
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[ps]
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- Evolutionary Function Approximation for Reinforcement Learning.
Shimon
Whiteson and Peter Stone.
Journal of Machine Learning Research,
7:877–917, May 2006.
Available from journal's web
page.
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[pdf]
(1.7MB
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[ps]
(6.1MB
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- Function Approximation via Tile Coding: Automating Parameter Choice.
Alexander
A. Sherstov and Peter Stone.
In J.-D. Zucker and I. Saitta,
editors, SARA 2005, Lecture Notes in Artificial Intelligence, pp. 194–205, Springer Verlag, Berlin, 2005.
SARA-05.
Official version from Publisher's
Webpage© Springer-Verlag
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[pdf]
(187.7kB
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[ps]
(583.4kB
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[slides.pdf]
(193.7kB
)
- Reinforcement Learning for RoboCup-Soccer Keepaway.
Peter Stone,
Richard S. Sutton, and Gregory
Kuhlmann.
Adaptive Behavior, 13(3):165–188, 2005.
Contains material that was previously published
in an ICML-2001 paper and a
RoboCup 2003 Symposium paper.
Some simulations
of keepaway referenced in the paper and keepaway software.
Details
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(1.2MB
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[ps]
(2.0MB
)
- Value Functions for RL-Based Behavior Transfer: A Comparative Study.
Matthew
E. Taylor, Peter Stone, and Yaxin
Liu.
In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
AAAI
2005
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(147.3kB
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[ps]
(449.9kB
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- Behavior Transfer for Value-Function-Based Reinforcement Learning.
Matthew
E. Taylor and Peter Stone.
In The Fourth International Joint
Conference on Autonomous Agents and Multiagent Systems, pp. 53–59, ACM Press, New York, NY, July 2005.
AAMAS-2005
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(230.4kB
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[ps]
(620.1kB
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- Machine Learning for Fast Quadrupedal Locomotion.
Nate Kohl and Peter
Stone.
In The Nineteenth National Conference on Artificial Intelligence, pp. 611–616, July 2004.
Some videos of walking robots referenced in
the paper.
AAAI 2004
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(210.0kB
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[ps]
(1.4MB
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- Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion.
Nate Kohl
and Peter Stone.
In Proceedings of the IEEE International Conference
on Robotics and Automation, May 2004.
Some videos
of walking robots referenced in the paper.
ICRA 2004
Details
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[pdf]
(301.5kB
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[ps]
(3.2MB
)
- Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer.
Gregory
Kuhlmann, Peter Stone, Raymond
Mooney, and Jude Shavlik.
In The AAAI-2004 Workshop on Supervisory
Control of Learning and Adaptive Systems, July 2004.
Details
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[pdf]
(170.3kB
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[ps]
(498.2kB
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- Adaptive Job Routing and Scheduling.
Shimon Whiteson
and Peter Stone.
Engineering Applications of Artificial Intelligence,
17(7):855–69, October 2004. Special issue on Autonomic Computing and Automation
Available from the publisher's
webpage
The version from this page corrects a minor error in the published version.
An earlier version appeared
in the proceedings of The Sixteenth Innovative Applications of Artificial
Intelligence Conference (IAAI 2004)
Details
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(664.7kB
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(1.1MB
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- TPOT-RL Applied to Network Routing.
Peter Stone.
In Proceedings
of the Seventeenth International Conference on Machine Learning, pp. 935–942, 2000.
ICML-2000
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(161.7kB
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(395.0kB
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- Team-Partitioned, Opaque-Transition Reinforcement Learning.
Peter Stone
and Manuela Veloso.
In Minoru
Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer
World Cup II, Lecture Notes in Artificial Intelligence, pp. 261–72, Springer Verlag, Berlin, 1999. Also in Proceedings
of the Third International Conference on Autonomous Agents, 1999
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(151.4kB
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Machine Learning: Transfer Learning
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
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(4.3MB
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- Task Phasing: Automated Curriculum Learning from Demonstrations.
Vaibhav Bajaj, Guni
Sharon, and Peter Stone.
In Proceedings of the 33rd International
Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
Accompanying code
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(416.0kB
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- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
Haresh
Karnan, Elvin Yang, Daniel Farkash, Garrett
Warnell, Joydeep Biswas, and Peter
Stone.
In The Conference on Robot Learning (CoRL), November 2023.
Poster,
Video, Project Website
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- Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis.
Zifan
Xu, Anirudh Nair, Xuesu Xiao, and Peter
Stone.
In IROS Workshop on Photorealistic Image and Environment Synthesis for Robotics (PIES-Rob) , January
2023.
Details
BibTeX
Download:
[pdf]
(4.3MB
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- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
Haresh
Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
Warnell, Peter Stone, and Joydeep Biswas.
In
International Conference on Intelligent Robots and Systems, 2022, October 2022.
Details
BibTeX
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[pdf]
(3.0MB
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- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
Haresh
Karnan, Garrett Warnell, Xuesu
Xiao, and Peter Stone.
In International Conference on Robotics and
Automation, 2022, May 2022.
Poster,
Video
Details
BibTeX
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[pdf]
(1.5MB
)
- Adversarial Imitation Learning from Video using a State Observer.
Haresh
Karnan, Garrett Warnell, Faraz
Torabi, and Peter Stone.
In International Conference on Robotics
and Automation, 2022, May 2022.
Video
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BibTeX
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[pdf]
(933.2kB
)
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
Josiah
P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
Warnell, and Peter Stone.
Special Issue on Reinforcement Learning
for Real Life, Machine Learning, 2021, May 2021.
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- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
Siddarth Desai, Ishan
Durugkar, Haresh Karnan, Garrett
Warnell, Josiah Hanna, and Peter
Stone.
In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
December 2020.
Poster
Details
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- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Siddharth Desai, Haresh
Karnan, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
11-minute video
presentation.
Details
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[pdf]
(1.9MB
)
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
Haresh
Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
14-minute video
presentation.
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[pdf]
(506.6kB
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- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
Sanmit
Narvekar, Bei Peng, Matteo Leonetti, Jivko
Sinapov, Matthew E. Taylor, and Peter
Stone.
Journal of Machine Learning Research, 21(181):1–50, 2020.
Details
BibTeX
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[pdf]
(1.4MB
)
- Generalizing Curricula for Reinforcement Learning.
Sanmit Narvekar
and Peter Stone.
In 4th Lifelong Learning Workshop at the International
Conference on Machine Learning (ICML 2020), July 2020.
Details
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[pdf]
(330.4kB
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[slides.pdf]
(3.8MB
)
- Learning Curriculum Policies for Reinforcement Learning.
Sanmit Narvekar
and Peter Stone.
In Proceedings of the 18th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
Details
BibTeX
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[pdf]
(953.0kB
)
[slides.pdf]
(5.6MB
)
- Agents teaching agents: a survey on inter-agent transfer learning.
Felipe Leno
Da Silva, Garrett Warnell, Anna
Helena Reali Costa, and Peter Stone.
Autonomous Agents and Multi-Agent
Systems, Dec 2019.
Official version from JAAMAS
Details
BibTeX
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[pdf]
(572.4kB
)
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
Felipe
Leno Da Silva, Anna Helena Reali Costa, and Peter
Stone.
In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
Details
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[pdf]
(1.6MB
)
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
Sanmit
Narvekar, Jivko Sinapov, and Peter
Stone.
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
2017.
Details
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[pdf]
(826.2kB
)
[slides.pdf]
(5.8MB
)
- Automatic Curriculum Graph Generation for Reinforcement Learning Agents.
Maxwell Svetlik, Matteo
Leonetti, Jivko Sinapov, Rishi Shah, Nick
Walker, and Peter Stone.
In Proceedings of the 31st AAAI Conference
on Artificial Intelligence (AAAI), February 2017.
Details
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[pdf]
(2.0MB
)
- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
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[pdf]
(917.9kB
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- Source Task Creation for Curriculum Learning.
Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti,
and Peter Stone.
In Proceedings of the 15th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
Details
BibTeX
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[pdf]
(630.0kB
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[slides.pdf]
(10.2MB
)
- Learning Inter-Task Transferability in the Absence of Target Task Samples.
Jivko
Sinapov, Sanmit Narvekar, Matteo
Leonetti, and Peter Stone.
In Proceedings of the International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
Details
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(337.2kB
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- An Introduction to Inter-task Transfer for Reinforcement Learning.
Matthew
E. Taylor and Peter Stone.
AI Magazine, 32(1):15–34,
2011.
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[pdf]
(237.0kB
)
[ps]
(773.0kB
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- Transfer Learning for Reinforcement Learning on a Physical Robot.
Samuel
Barrett, Matt E. Taylor, and Peter
Stone.
In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents
Workshop (AAMAS - ALA), May 2010.
AAMAS ALA 2010
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(688.8kB
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[ps]
(5.7MB
)
- Boosting for Regression Transfer.
David Pardoe and Peter
Stone.
In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
Some
of the data used in the experiments.
Details
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(600.5kB
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[ps]
(1.7MB
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- Transfer Learning for Reinforcement Learning Domains: A Survey.
Matthew
E. Taylor and Peter Stone.
Journal of Machine Learning Research,
10(1):1633–1685, 2009.
Official version
from journal website.
Details
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[pdf]
(399.8kB
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[ps]
(579.4kB
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- Transferring Instances for Model-Based Reinforcement Learning.
Matthew E. Taylor,
Nicholas K. Jong, and Peter
Stone.
In Machine Learning and Knowledge Discovery in Databases, pp. 488–505, September 2008.
Official
version from Publisher's Webpage© Springer-Verlag
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[pdf]
(304.9kB
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[ps]
(860.1kB
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- Autonomous Transfer for Reinforcement Learning.
Matthew E. Taylor,
Gregory Kuhlmann, and Peter
Stone.
In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
AAMAS-2008
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[ps]
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- Transfer Learning and Intelligence: an Argument and Approach.
Matthew E. Taylor,
Gregory Kuhlmann, and Peter
Stone.
In Proceedings of the First Conference on Artificial General Intelligence, March 2008.
AGI-2008
Google
video version of the conference presentation.
Details
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[pdf]
(149.0kB
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[ps]
(202.5kB
)
- General Game Learning using Knowledge Transfer.
Bikramjit Banerjee
and Peter Stone.
In The 20th International Joint Conference on Artificial
Intelligence, pp. 672–677, January 2007.
IJCAI-07
Details
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[pdf]
(118.1kB
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[ps]
(198.5kB
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- Graph-Based Domain Mapping for Transfer Learning in General Games.
Gregory
Kuhlmann and Peter Stone.
In Proceedings of The Eighteenth European
Conference on Machine Learning, September 2007.
Details
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(377.0kB
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[ps]
(601.6kB
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- Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
Matthew
E. Taylor, Peter Stone, and Yaxin
Liu.
Journal of Machine Learning Research, 8(1):2125–2167, 2007.
Available from journal's
web page.
Details
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(499.9kB
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[ps]
(831.3kB
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- Cross-Domain Transfer for Reinforcement Learning.
Matthew E. Taylor
and Peter Stone.
In Proceedings of the Twenty-Fourth International
Conference on Machine Learning, June 2007.
ICML
2007
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(220.7kB
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[ps]
(325.4kB
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- Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning.
Matthew
E. Taylor, Shimon Whiteson, and Peter
Stone.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
AAMAS-2007
Details
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(222.5kB
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[ps]
(525.2kB
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- Representation Transfer for Reinforcement Learning.
Matthew E. Taylor
and Peter Stone.
In AAAI 2007 Fall Symposium on Computational
Approaches to Representation Change during Learning and Development, November 2007.
2007
AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development
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[ps]
(375.1kB
)
- Accelerating Search with Transferred Heuristics.
Matthew E. Taylor,
Gregory Kuhlmann, and Peter
Stone.
In ICAPS-07 workshop on AI Planning and Learning, September 2007.
ICAPS
2007 workshop on AI Planning and Learning
Details
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(139.9kB
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[ps]
(215.4kB
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- Value Function Transfer for General Game Playing.
Bikramjit Banerjee,
Gregory Kuhlmann, and Peter
Stone.
In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
ICML
2006 workshop on Structural Knowledge Transfer for Machine Learning
Details
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(172.9kB
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[ps]
(464.0kB
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- Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping.
Yaxin
Liu and Peter Stone.
In Proceedings of the Twenty-First National
Conference on Artificial Intelligence, pp. 415–20, July 2006.
AAAI
2006
Details
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(151.7kB
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[ps]
(1.6MB
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- State Abstraction Discovery from Irrelevant State Variables.
Nicholas
K. Jong and Peter Stone.
In Proceedings of the Nineteenth International
Joint Conference on Artificial Intelligence, pp. 752–757, August 2005.
Details
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[pdf]
(102.1kB
)
[ps]
(249.8kB
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[slides.pdf]
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- Improving Action Selection in MDP's via Knowledge Transfer.
Alexander
A. Sherstov and Peter Stone.
In Proceedings of the Twentieth
National Conference on Artificial Intelligence, July 2005.
AAAI
2005
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(774.2kB
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- Value Functions for RL-Based Behavior Transfer: A Comparative Study.
Matthew
E. Taylor, Peter Stone, and Yaxin
Liu.
In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
AAAI
2005
Details
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[pdf]
(147.3kB
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[ps]
(449.9kB
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- Behavior Transfer for Value-Function-Based Reinforcement Learning.
Matthew
E. Taylor and Peter Stone.
In The Fourth International Joint
Conference on Autonomous Agents and Multiagent Systems, pp. 53–59, ACM Press, New York, NY, July 2005.
AAMAS-2005
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[ps]
(620.1kB
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Machine Learning: Imitation Learning
- Telemoma: A Modular and Versatile Teleoperation System for Mobile Manipulation.
Shivin Dass, Wensi Ai, Yuqian
Jiang, Samik Singh, Jiaheng Hu,
Ruohan Zhang, Peter Stone,
Ben Abbatematteo, and Roberto Martin-Martin.
In ICRA Workshop on Mobile Manipulation and Embodied Intelligence,
May 2024.
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- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
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(2.0MB
)
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
William Yue,
Bo Liu, and Peter Stone.
In
Conference on Lifelong Learning Agents (CoLLAs), July 2024.
Details
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[pdf]
(599.7kB
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[poster.pdf]
(709.1kB
)
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
Haresh
Karnan, Elvin Yang, Daniel Farkash, Garrett
Warnell, Joydeep Biswas, and Peter
Stone.
In The Conference on Robot Learning (CoRL), November 2023.
Poster,
Video, Project Website
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- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
Bo
Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
Zhu, and Peter Stone.
In 37th Conference on Neural Information Processing
Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
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(37.6MB
)
[poster.pdf]
(2.6MB
)
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
Caroline
Wang, Garrett Warnell, and Peter
Stone.
In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
May 2023.
Details
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[pdf]
(1.6MB
)
[slides.pdf]
(2.4MB
)
[poster.pdf]
(1.4MB
)
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
Caroline
Wang, Ishan Durugkar, Elad Liebman,
and Peter Stone.
In Proceedings of the 37th AAAI Conference on Artificial
Intelligence (AAAI-23), February 2023.
Details
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[pdf]
(801.2kB
)
[slides.pdf]
(3.7MB
)
[poster.pdf]
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)
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
Yifeng
Zhu, Zhenyu Jiang, Peter Stone, and Yuke
Zhu.
In Conference on Robot Learning (CoRL), November 2023.
Details
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[pdf]
(7.3MB
)
[poster.pdf]
(5.2MB
)
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
Eddy Hudson, Garrett
Warnell, Faraz Torabi, and Peter
Stone.
In International Conference on Robotics and Automation (ICRA), May 2022.
Presentation
Video
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- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
Details
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[pdf]
(4.2MB
)
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
Haresh
Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
Warnell, Peter Stone, and Joydeep Biswas.
In
International Conference on Intelligent Robots and Systems, 2022, October 2022.
Details
BibTeX
Download:
[pdf]
(3.0MB
)
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
Haresh
Karnan, Garrett Warnell, Xuesu
Xiao, and Peter Stone.
In International Conference on Robotics and
Automation, 2022, May 2022.
Poster,
Video
Details
BibTeX
Download:
[pdf]
(1.5MB
)
- Adversarial Imitation Learning from Video using a State Observer.
Haresh
Karnan, Garrett Warnell, Faraz
Torabi, and Peter Stone.
In International Conference on Robotics
and Automation, 2022, May 2022.
Video
Details
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[pdf]
(933.2kB
)
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
Yifeng
Zhu, Peter Stone, and Yuke
Zhu.
IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
Project page
Code
Details
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[pdf]
(9.3MB
)
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
Yifeng
Zhu, Abhishek Joshi, Peter Stone, and Yuke
Zhu.
In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
Project page
Code
Details
BibTeX
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(4.4MB
)
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
Eddy Hudson, Garrett
Warnell, and Peter Stone.
In Autonomous Robots and Multirobot Systems
Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
Details
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(393.0kB
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- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
Faraz
Torabi, Garrett Warnell, and Peter
Stone.
In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
2021.
Video presentation
Details
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[pdf]
(742.7kB
)
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
Zizhao
Wang, Xuesu Xiao, Bo Liu,
Garrett Warnell, and Peter
Stone.
IEEE Robotics and Automation Letters (RA-L), October 2021.
5-minute
Video Presentation; 15-minute Video Presentation
Details
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[pdf]
(1.1MB
)
[slides.pdf]
(2.7MB
)
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
Zizhao
Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
In Proceedings
of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
1-minute
Video Summary; 15-minute Video Presentation
Details
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[pdf]
(2.9MB
)
[slides.pdf]
(2.7MB
)
- APPLI: Adaptive Planner Parameter Learning From Interventions.
Zizhao Wang,
Xuesu Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
In Proceedings of the International Conference
on Robotics and Automation (ICRA 2021), May 2021.
Video presentation
Details
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[pdf]
(4.2MB
)
- Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain.
Xuesu
Xiao, Joydeep Biswas, and Peter Stone.
IEEE
Robotics and Automation Letters (RA-L), July 2021.
Contains material that was previously presented in an ICRA21
workshop paper Video
Details
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[pdf]
(3.2MB
)
[slides.pdf]
(23.2MB
)
- Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
IEEE Robotics and Automation Letters (RA-L),
January 2021.
5-minute video demonstration
Project
webpage
Details
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[pdf]
(3.2MB
)
- Agile Robot Navigation through Hallucinated Learning and Sober Deployment.
Xuesu
Xiao, Bo Liu, and Peter Stone.
In
Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
Video
Details
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(3.1MB
)
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
Brahma
Pavse, Faraz Torabi, Josiah
Hanna, Garrett Warnell, and Peter
Stone.
IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
Video
of the experiments; 13-minute video presentation.
Details
BibTeX
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[pdf]
(405.1kB
)
[slides.pptx]
(115.4MB
)
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, Jonathan Fink, and Peter Stone.
IEEE Robotics and Automation
Letters (RA-L), June 2020.
Presented at International Conference on Intelligent Robots and Systems ({IROS})\\
5-minute Video presentation; 15-minute
Video presentation
Project webpage
Details
BibTeX
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[pdf]
(2.2MB
)
[slides.pdf]
(21.1MB
)
- Agents teaching agents: a survey on inter-agent transfer learning.
Felipe Leno
Da Silva, Garrett Warnell, Anna
Helena Reali Costa, and Peter Stone.
Autonomous Agents and Multi-Agent
Systems, Dec 2019.
Official version from JAAMAS
Details
BibTeX
Download:
[pdf]
(572.4kB
)
- Imitation Learning from Video by Leveraging Proprioception.
Faraz
Torabi, Garrett Warnell, and Peter
Stone.
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
2019.
Details
BibTeX
Download:
[pdf]
(1.1MB
)
[slides.pptx]
(20.3MB
)
- Recent Advances in Imitation Learning from Observation.
Faraz Torabi,
Garrett Warnell, and Peter
Stone.
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
2019.
Details
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[pdf]
(157.4kB
)
[slides.pptx]
(45.5MB
)
- Generative Adversarial Imitation from Observation.
Faraz Torabi,
Garrett Warnell, and Peter
Stone.
In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
Details
BibTeX
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[pdf]
(1.0MB
)
- Sample-efficient Adversarial Imitation Learning from Observation.
Faraz
Torabi, Sean Geiger, Garrett Warnell, and Peter
Stone.
In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
Details
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(6.1MB
)
- Behavioral Cloning from Observation.
Faraz Torabi, Garrett
Warnell, and Peter Stone.
In Proceedings of the 27th International
Joint Conference on Artificial Intelligence (IJCAI), July 2018.
Also available from arXiv
Details
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(2.3MB
)
[slides.pptx]
(26.0MB
)
Machine Learning: Learning from Humans
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
Details
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)
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
W. Bradley
Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
Stone, and Scott Niekum.
In The 38th Annual AAAI Conference on Artificial
Intelligence (AAAI), February 2024.
Details
BibTeX
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[pdf]
(3.6MB
)
[slides.pdf]
(3.9MB
)
[poster.pdf]
(2.9MB
)
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
Details
BibTeX
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[pdf]
(2.0MB
)
- The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications.
Serena
Booth, W Bradley Knox, Julie Shah, Scott
Niekum, Peter Stone, and Alessandro Allievi.
In Proceedings of the
37th AAAI Conference on Artificial Intelligence (AAAI), Feb 2023.
Project
page with slides and video.
Details
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(1.4MB
)
- Models of human preference for learning reward functions.
W. Bradley Knox,
Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
Stone, and Alessandro Allievi.
Transactions on Machine Learning Research (TMLR), 2023.
Details
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[pdf]
(6.7MB
)
[slides.pdf]
(13.4MB
)
- Reward (Mis)design for Autonomous Driving.
W. Bradley Knox, Alessandro Allievi,
Holger Banzhaf, Felix Schmitt, and Peter Stone.
Artificial Intelligence,
316:103829, 2023.
Paper webpage
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- Visually Adaptive Geometric Navigation.
Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
Xiao, Garrett Warnell, Joydeep
Biswas, and Peter Stone.
In IEEE International Symposium on Safety,Security,and
Rescue Robotics, November 2023.
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(4.8MB
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- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
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- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
Zizhao
Wang, Xuesu Xiao, Bo Liu,
Garrett Warnell, and Peter
Stone.
IEEE Robotics and Automation Letters (RA-L), October 2021.
5-minute
Video Presentation; 15-minute Video Presentation
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(1.1MB
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[slides.pdf]
(2.7MB
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- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
Zizhao
Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
In Proceedings
of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
1-minute
Video Summary; 15-minute Video Presentation
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- APPLI: Adaptive Planner Parameter Learning From Interventions.
Zizhao Wang,
Xuesu Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
In Proceedings of the International Conference
on Robotics and Automation (ICRA 2021), May 2021.
Video presentation
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- Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks.
Ruohan
Zhang, Faraz Torabi, Garrett
Warnell, and Peter Stone.
Autonomous Agents and Multi-Agent Systems,
35(31), June 2021.
official online version
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(3.8MB
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- The EMPATHIC Framework for Task Learning from Implicit Human Feedback.
Yuchen
Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott
Niekum, and W. Bradley Knox.
In Proceedings of the 4th Conference on Robot
Learning (CoRL 2020), November 2020.
5-minute video presentation;
47-minute in-depth talk.
Project website.
Raw
data from experiments.
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(6.4MB
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(59.4MB
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- Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
Jesse
Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
Walker, Yuqian Jiang, Harel
Yedidsion, Justin Hart, Peter Stone,
and Raymond J. Mooney.
The Journal of Artificial Intelligence Research
(JAIR), 67, February 2020.
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(4.0MB
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- APPLD: Adaptive Planner Parameter Learning from Demonstration.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, Jonathan Fink, and Peter Stone.
IEEE Robotics and Automation
Letters (RA-L), June 2020.
Presented at International Conference on Intelligent Robots and Systems ({IROS})\\
5-minute Video presentation; 15-minute
Video presentation
Project webpage
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[slides.pdf]
(21.1MB
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- Agents teaching agents: a survey on inter-agent transfer learning.
Felipe Leno
Da Silva, Garrett Warnell, Anna
Helena Reali Costa, and Peter Stone.
Autonomous Agents and Multi-Agent
Systems, Dec 2019.
Official version from JAAMAS
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- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
Jesse
Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
Walker, Yuqian Jiang, Harel
Yedidsion, Justin Hart, Peter Stone,
and Raymond Mooney.
In Proceedings of the International Conference on
Robotics and Automation (ICRA 2019), May 2019.
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(1.6MB
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- Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
Garrett
Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
In Proceedings
of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
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(1.6MB
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[slides.pptx]
(16.2MB
)
- Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
W. Bradley Knox and Peter Stone.
Artificial
Intelligence, 225(), August 2015.
Artificial
Intelligence
Contains material that was previously published in a IUI 2013 paper and a RoMan 2012 paper that was nominated as a CoTeSys Cognitive Robotics BEST PAPER AWARD FINALIST.
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- Training a Robot via Human Feedback: A Case Study.
W. Bradley Knox, Peter
Stone, and Cynthia Breazeal.
In International Conference on
Social Robotics, October 2013.
BEST PAPER AWARD WINNER at ICSR 2013
An
associated video summarizing the paper (direct
link).
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- How Humans Teach Agents: A New Experimental Perspective.
W. Bradley Knox,
Brian D. Glass, Bradley
C. Love, W. Todd Maddox, and Peter
Stone.
International Journal of Social Robotics, 4:409–421, Springer Netherlands, October 2012. 10.1007/s12369-012-0163-x
International Journal of Social Robotics
Download article from publisher
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- The Nature of Belief-Directed Exploratory Choice in Human Decision-Making.
W.
Bradley Knox, A. Ross Otto, Peter
Stone, and Bradley Love.
Frontiers in Psychology, 2(398), January 2012.
Frontiers in Psychology
Download
article from publisher (free)
A follow-up
commentary by Erica Yu.
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(unavailable)
- Reinforcement Learning from Simultaneous Human and MDP Reward.
W. Bradley Knox
and Peter Stone.
In Proceedings of the 11th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
AAMAS 2012
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- Learning from feedback on actions past and intended.
W. Bradley Knox,
Cynthia Breazeal, and Peter
Stone.
In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports
Session (HRI), March 2012.
HRI 2012
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(3.9MB
)
- Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report.
W. Bradley
Knox and Peter Stone.
In IJCAI 2011 Workshop on Agents Learning Interactively
from Human Teachers (ALIHT), July 2011.
IJCAI 2011 Workshop
on Agents Learning Interactively from Human Teachers (ALIHT)
Details
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[pdf]
(372.4kB
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[ps]
(41.6MB
)
- Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning.
W. Bradley
Knox and Peter Stone.
In Proc. of 9th Int. Conf. on Autonomous Agents
and Multiagent Systems (AAMAS 2010), May 2010.
Winner of the Pragnesh Jay Modi BEST STUDENT PAPER AWARD (and
best paper award nominee).
The TAMER project page with videos
of TAMER in action.
AAMAS-2010
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- Interactively Shaping Agents via Human Reinforcement: The TAMER Framework.
W. Bradley
Knox and Peter Stone.
In The Fifth International Conference on Knowledge
Capture, September 2009.
The TAMER project page with
videos of TAMER in action.
K-CAP
2009
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- Design Principles for Creating Human-Shapable Agents.
W. Bradley Knox,
Ian Fasel, and Peter
Stone.
In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
AAAI
Spring 2009 Symposium: Agents that Learn from Human Teachers
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(400.8kB
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(2.1MB
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- TAMER: Training an Agent Manually via Evaluative Reinforcement.
W. Bradley
Knox and Peter Stone.
In IEEE 7th International Conference on Development
and Learning, August 2008.
ICDL-2008
Also available in IEEE
Xplore, 9-12 Aug. 2008 Pages:292 - 297
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(12.8MB
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Machine Learning: Lifelong Learning
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
William Yue,
Bo Liu, and Peter Stone.
In
Conference on Lifelong Learning Agents (CoLLAs), July 2024.
Details
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[pdf]
(599.7kB
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[poster.pdf]
(709.1kB
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- A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems.
Megan M. Baker, Alexander New, Mario
Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Ese Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown,
Zachary Daniels, Anurag Daram, Fabien Delattre, Ryan Dellana, Eric Eaton,
Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris,
Dhireesha Kudithipudi, Erik Learned-Miller, Seungwon Lee,
Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine
D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan,
Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang,
Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel
Yedidsion, Shangqun Yu, and Gautam K. Vallabha.
Neural Networks, pp. 274–96, March 2023.
Available
from https://arxiv.org/abs/2301.07799
Official version on publisher's website
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- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
Bo
Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
Zhu, and Peter Stone.
In 37th Conference on Neural Information Processing
Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
Details
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(37.6MB
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[poster.pdf]
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- Continual Learning and Private Unlearning.
Bo Liu, Qiang Liu, and Peter Stone.
In Proceedings of the 1st Conference on Lifelong Learning Agents
(CoLLA), August 2022.
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(440.4kB
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[slides.pdf]
(710.5kB
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- A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects.
Shahaf Shperberg, Bo
Liu, Allessandro Allievi, and Peter Stone.
In Proceedings of the
1st Conference on Lifelong Learning Agents (CoLLA), August 2022.
Details
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)
Multi-Robot Systems
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
Yoonchang
Sung, Rahul Shome, and Peter Stone.
In IEEE International Conference
on Robotics and Automation (ICRA), March 2024.
Video
presentation
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- Program Embeddings for Rapid Mechanism Evaluation.
Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
and Peter Stone.
In ICRA Workshop on Multi-Robot Learning, May 2023.
Details
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(1.3MB
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[poster.pdf]
(916.2kB
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- Quantifying Human Rationality in Ad-hoc Teamwork.
Yair Hanina, Reuth
Mirsky, William Macke, and Peter
Stone.
In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
Details
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- UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
Patrick
MacAlpine, Bo Liu, William Macke,
Caroline Wang, and Peter Stone.
In
Rachid Alami, Joydeep Biswas, Maya
Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International
Publishing, 2022.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021
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- Learning to Improve Multi-Robot Hallway Navigation.
Jin-Soo Park, Brian Tsang, Harel
Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
In Proceedings of the 4th Conference on Robot Learning (CoRL),
November 2020.
Video presentation
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- Multi-Robot Planning with Conflicts and Synergies.
Yuqian Jiang, Harel
Yedidsion, Shiqi Zhang, Guni
Sharon, and Peter Stone.
Autonomous Robots, Springer, March 2019.
Official version from Publisher's Webpage
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- UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, and Peter Stone.
In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn,
and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pp.
540–52, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2019
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(3.8MB
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- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, John Sigmon, and Peter Stone.
In Dirk Holz, Katie
Genter, Maarouf Saad, and Oskar von Stryk, editors,
RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pp. 462–75, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2018
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(6.0MB
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- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
Harel
Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
Stone, and Raymond Mooney.
In International Conference on Social
Robotics (ICSR), pp. 133–143, November 2019.
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- Overlapping Layered Learning.
Patrick MacAlpine and Peter
Stone.
Artificial Intelligence, 254:21–43, Elsevier, January 2018.
Official version from Publisher's
Webpage
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
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- UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Claude Sammut, Oliver Obst, Flavio Tonidandel,
and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, Lecture Notes in Artificial Intelligence, pp.
473–85, Springer, 2018.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2017
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- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
Ad Hoc Teamwork Robotics Competition.
Katie Genter, Tim
Laue, and Peter Stone.
Autonomous Agents and Multi-Agent Systems
(JAAMAS), 31(4):790–820, Springer, July 2017.
Official version from Publisher's
Webpage
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- UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 515–28, Springer, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2016
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- Prioritized Role Assignment for Marking.
Patrick MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 306–18, Springer Verlag, Berlin, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/html/marking.html
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)
[ps]
(13.5MB
)
[slides.pdf]
(157.3MB
)
- UT Austin Villa RoboCup 3D Simulation Base Code Release.
Patrick MacAlpine
and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
Code release at https://github.com/LARG/utaustinvilla3d
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(394.2kB
)
[ps]
(2.1MB
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[slides.pdf]
(107.1MB
)
- UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine, Josiah Hanna, Jason
Liang, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2015
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(7.2MB
)
- Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League.
Mike Depinet, Patrick MacAlpine,
and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian
Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial
Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/learningFromObservation.html
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(42.3MB
)
- Leading the Way: An Efficient Multi-robot Guidance System.
Piyush Khandelwal,
Samuel Barrett, and Peter Stone.
In
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
Accompanying videos at
https://www.youtube.com/watch?v=os1BjHgM5ao&feature=youtu.be
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(694.2kB
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- UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Mike Depinet, Jason
Liang, and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot
Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos
at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2014
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(1.9MB
)
- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
Patrick
MacAlpine, Mike Depinet, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
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(2.5MB
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[slides.pdf]
(105.3MB
)
- SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning.
Patrick
MacAlpine, Eric Price, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/scram.html
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(260.3kB
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[ps]
(676.5kB
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[slides.pdf]
(40.3MB
)
- Multi-robot Human Guidance using Topological Graphs.
Piyush Khandelwal
and Peter Stone.
In AAAI Spring 2014 Symposium on Qualitative Representations
for Robots (AAAI-SSS), March 2014.
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(1.1MB
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(7.6MB
)
- Planning in Answer Set Programming while Learning Action Costs for Mobile Robots.
Fangkai
Yang, Piyush Khandelwal, Matteo
Leonetti, and Peter Stone.
In AAAI Spring 2014 Symposium on Knowledge
Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
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(643.4kB
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(5.3MB
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- On Coordination in Practical Multi-Robot Patrol.
Noa Agmon, Chien-Liang
Fok, Yehuda Emaliah, Peter
Stone, Christine Julien, and Sriram
Vishwanath.
In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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- A Platform for Evaluating Autonomous Intersection Management Policies.
Chien-Liang
Fok, Maykel Hanna, Seth Gee, Tsz-Chiu
Au, Peter Stone, Christine
Julien, and Sriram Vishwanath.
In Proceedings
of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.
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(61.7MB
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- Multiagent Patrol Generalized to Complex Environmental Conditions.
Noa Agmon,
Daniel Urieli, and Peter Stone.
In
Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
Extended
version, book
chapter
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- Dynamic Lane Reversal in Traffic Management.
Matthew Hausknecht,
Tsz-Chiu Au, Peter Stone, David
Fajardo, and Travis Waller.
In Proceedings of IEEE Intelligent Transportation
Systems Conference (ITSC), 2011.
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(127.0kB
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(4.3MB
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- Connectivity-based Localization in Robot Networks.
Tobias Jung,
Mazda Ahmadi, and Peter
Stone.
In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
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- Multiagent Interactions in Urban Driving.
Patrick Beeson, Jack
O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter
Stone.
Journal of Physical Agents, 2(1):15–30, March 2008. Special issue on Multi-Robot Systems
JoPhA
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- Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots.
Mazda
Ahmadi and Peter Stone.
In Proceedings of the Twenty-First National
Conference on Artificial Intelligence, pp. 580–85, July 2006.
AAAI
2006.
Additional details on the distributed "biconnected check" can be found in Keeping
in Touch: A Distributed Check for Biconnected Structure by Homogeneous Robots in the 2006 International Symposium
on Distributed Autonomous Robotic Systems (DARS 2006).
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- A Multi-Robot System for Continuous Area Sweeping Tasks.
Mazda
Ahmadi and Peter Stone.
In Proceedings of the IEEE International
Conference on Robotics and Automation, pp. 1724–1729, May 2006.
Some videos
of the robot referenced in the paper.
ICRA 2006
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Multiagent Systems
- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
Arrasy
Rahman, Jiaxun Cui, and Peter Stone.
In
AAAI, February 2024.
the conference presentation
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- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
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- A collective AI via lifelong learning and sharing at the edge.
Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir
Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan
How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven
Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash,
Vishwa Parekh, Kaushik Roy, Shahaf Shperberg, Hava T. Siegelmann, Peter Stone,
Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, and Soheil Kolouri.
nature
machine intelligence, 2024.
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- N-Agent Ad Hoc Teamwork.
Caroline Wang, Arrasy
Rahman, Ishan Durugkar, Elad
Liebman, and Peter Stone.
In Conference on Neural Information Processing
Systems (NeurIPS), December 2024.
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- MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection.
Jiaxun
Cui, Xiaomeng Yang, Mulong Luo, Geunbae
Lee, Peter Stone, Hsien-Hsin
S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, and
Yuandong Tian.
In The Eleventh International Conference on Learning
Representations (ICLR), May 2023.
Video presentation
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- Program Embeddings for Rapid Mechanism Evaluation.
Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
and Peter Stone.
In ICRA Workshop on Multi-Robot Learning, May 2023.
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- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
Jinsoo Park, Xuesu
Xiao, Garrett Warnell, Harel
Yedidsion, and Peter Stone.
In Proceedings of the 2023 IEEE International
Conference on Robotics and Automation (ICRA 2023), May 2023.
6-minute video
presentation
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- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
Caroline
Wang, Ishan Durugkar, Elad Liebman,
and Peter Stone.
In Proceedings of the 37th AAAI Conference on Artificial
Intelligence (AAAI-23), February 2023.
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(801.2kB
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- Quantifying Human Rationality in Ad-hoc Teamwork.
Yair Hanina, Reuth
Mirsky, William Macke, and Peter
Stone.
In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
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- UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
Patrick
MacAlpine, Bo Liu, William Macke,
Caroline Wang, and Peter Stone.
In
Rachid Alami, Joydeep Biswas, Maya
Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International
Publishing, 2022.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021
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- A Survey of Ad Hoc Teamwork Research.
Reuth Mirsky, Ignacio
Carlucho, Arrasy Rahman, Eliott Fosong, William
Macke, Mohan Sridharan, Peter
Stone, and Stefano Albrecht.
In Baumeister, Dorothea and Rothe, Jörg, editors,
Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
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- Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings.
Kingsley Nweye, Bo
Liu, Nagy Zoltan, and Peter Stone.
Journal of Energy and AI, 2022,
September 2022.
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- Reasoning about Human Behavior in Ad Hoc Teamwork.
Jennifer Suriadinata, William
Macke, Reuth Mirsky, and Peter
Stone.
In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
Video
Presentation
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- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
Harel
Yedidsion, Shani Alkoby, and Peter
Stone.
Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
arXiv
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- UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, and Peter Stone.
In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn,
and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pp.
540–52, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2019
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- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, John Sigmon, and Peter Stone.
In Dirk Holz, Katie
Genter, Maarouf Saad, and Oskar von Stryk, editors,
RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pp. 462–75, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2018
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- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
Guni
Sharon, Stephen D. Boyles, Shani
Alkoby, and Peter Stone.
In Proceedings of the 18th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
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- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
Haipeng
Chen, Bo An, Guni Sharon, Josiah
P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
In Proceedings
of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
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- Overlapping Layered Learning.
Patrick MacAlpine and Peter
Stone.
Artificial Intelligence, 254:21–43, Elsevier, January 2018.
Official version from Publisher's
Webpage
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
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- UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Claude Sammut, Oliver Obst, Flavio Tonidandel,
and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, Lecture Notes in Artificial Intelligence, pp.
473–85, Springer, 2018.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2017
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- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
Tarun
Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
and Peter Stone.
Transportation Research Part B: Methodological,
110:104–21, 2018.
Official version from Publisher's
Webpage
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- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
Guni
Sharon, Michael Albert, Tarun
Rambha, Stephen Boyles, and Peter
Stone.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
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- Multiagent Learning Paradigms.
Karl Tuyls and Peter Stone.
In
Francesco Belardinelli and Estefania Argente, editors, Multi-Agent Systems and Agreement Technologies, Lecture Notes
in Artificial Intelligence, pp. 3–21, Springer, 2018.
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- Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?.
Michael
Albert, Vincent Conitzer, and Peter Stone.
In Proceedings of the
16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
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- Automated Design of Robust Mechanisms.
Michael Albert, Vincent
Conitzer, and Peter Stone.
In Proceedings of the Thirty-First AAAI Conference
on Artificial Intelligence (AAAI-17), Feb 2017.
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(366.4kB
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- UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 515–28, Springer, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2016
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- Prioritized Role Assignment for Marking.
Patrick MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 306–18, Springer Verlag, Berlin, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/html/marking.html
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[pdf]
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)
[ps]
(13.5MB
)
[slides.pdf]
(157.3MB
)
- UT Austin Villa RoboCup 3D Simulation Base Code Release.
Patrick MacAlpine
and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
Code release at https://github.com/LARG/utaustinvilla3d
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(394.2kB
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[ps]
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- Network-wide Adaptive Tolling for Connected and Automated vehicles.
Guni
Sharon, Michael W. Levin, Josiah
P. Hanna, Tarun Rambha, Stephen
D. Boyles, and Peter Stone.
Transportation Research Part C, 84:142–157,
September 2017.
Transportation Research Part C.
Audio slides.
Contains material
that was previously published in an AAMAS-17 paper.
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- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
Guni
Sharon and Peter Stone.
In Gita Sukthankar and Juan
A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
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- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
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- UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine, Josiah Hanna, Jason
Liang, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2015
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- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
Daniel
Urieli and Peter Stone.
In Proceedings of the 15th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
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- Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
Daniel
Urieli and Peter Stone.
In Proceedings of the 30th Conference on
Artificial Intelligence (AAAI 2016), February 2016.
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- Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork.
Samuel
Barrett and Peter Stone.
In Proceedings of the Twenty-Ninth AAAI
Conference on Artificial Intelligence, January 2015.
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- Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League.
Mike Depinet, Patrick MacAlpine,
and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian
Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial
Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/learningFromObservation.html
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- When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing.
Fei
Fang, Peter Stone, and Milind
Tambe.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
Winner of Computational Sustainability Track Outstanding Paper Award at IJCAI 2015
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- Determining Placements of Influencing Agents in a Flock.
Katie Genter,
Shun Zhang, and Peter Stone.
In
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
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- UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Mike Depinet, Jason
Liang, and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot
Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos
at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2014
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- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
Patrick
MacAlpine, Mike Depinet, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
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[slides.pdf]
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- SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning.
Patrick
MacAlpine, Eric Price, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/scram.html
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- Modeling Uncertainty in Leading Ad Hoc Teams.
Noa Agmon, Samuel
Barrett, and Peter Stone.
In Proc. of 13th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2014.
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- Communicating with Unknown Teammates.
Samuel Barrett, Noa
Agmon, Noam Hazon, Sarit Kraus,
and Peter Stone.
In Proceedings of the Twenty-First European Conference
on Artificial Intelligence, August 2014.
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- Teamwork with Limited Knowledge of Teammates.
Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
In Proceedings of the Twenty-Seventh AAAI Conference on
Artificial Intelligence, July 2013.
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- An Analysis Framework for Ad Hoc Teamwork Tasks.
Samuel Barrett
and Peter Stone.
In Proceedings of the 11th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
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- A Platform for Evaluating Autonomous Intersection Management Policies.
Chien-Liang
Fok, Maykel Hanna, Seth Gee, Tsz-Chiu
Au, Peter Stone, Christine
Julien, and Sriram Vishwanath.
In Proceedings
of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.
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- Multiagent Patrol Generalized to Complex Environmental Conditions.
Noa Agmon,
Daniel Urieli, and Peter Stone.
In
Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
Extended
version, book
chapter
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- Enforcing Liveness in Autonomous Traffic Management.
Tsz-Chiu Au, Neda Shahidi, and Peter
Stone.
In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
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- Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
Samuel
Barrett and Peter Stone.
In Tenth International Conference on Autonomous
Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
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(136.1kB
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- Dynamic Lane Reversal in Traffic Management.
Matthew Hausknecht,
Tsz-Chiu Au, Peter Stone, David
Fajardo, and Travis Waller.
In Proceedings of IEEE Intelligent Transportation
Systems Conference (ITSC), 2011.
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- Comparing Agents: Success against People in Security Domains.
Raz Lin,
Sarit Kraus, Noa Agmon, Samuel
Barrett, and Peter Stone.
In Proceedings of the Twenty-Fifth AAAI
Conference on Artificial Intelligence, August 2011.
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- Flood Disaster Mitigation: A Real-world Challenge Problem forMulti-Agent Unmanned Surface Vehicles.
Paul
Scerri, Balajee Kannan, Pras Velagapudi, Kate Macarthur, Peter Stone, Matthew E. Taylor, John Dolan, Alessandro Farinelli, Archie Chapman, Bernadine
Dias, and George Kantor.
In Proceedings of the Autonomous Robots and MultirobotSystems workshop (at AAMAS-11),
May 2011.
ARMS-11
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- Proceedings of the Tenth International Conference on Autonomous Agents and Multiagent Systems,
Kagan
Tumer, Pinar Yolum, Liz
Sonenberg, and Peter Stone, editors.
International Foundation for Autonomous
Agents and Multiagent Systems (IFAAMAS), May 2011.
A book based on AAMAS 2011
ISBN-10: 0-9826571-5-3 ISBN-13 978-0-9826571-5-7
on-line
version from IFAAMAS.
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(unavailable)
- Online Multiagent Learning against Memory Bounded Adversaries.
Doran
Chakraborty and Peter Stone.
In Machine Learning and Knowledge Discovery
in Databases, pp. 211–26, September 2008.
Official version from Publisher's
Webpage© Springer-Verlag
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- Sharing the Road: Autonomous Vehicles meet Human Drivers.
Kurt
Dresner and Peter Stone.
In The 20th International Joint Conference
on Artificial Intelligence, pp. 1263–68, January 2007.
IJCAI-07
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(189.9kB
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- Multiagent learning is not the answer. It is the question.
Peter Stone.
Artificial
Intelligence, 171:402–05, May 2007.
Response to Shoham, Powers, and Grenager If Multi-Agent Systems is
the Answer, What is the Question?, available from Shoham's webpage.
Official version from the AIJ
publisher's webpage.
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- Learning and Multiagent Reasoning for Autonomous Agents.
Peter Stone.
In
The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
IJCAI-07
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- Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management.
Kurt
Dresner and Peter Stone.
In AAMAS 2006 Workshop on Agents in Traffic
and Transportation, May 2006.
ATT 2006.
The project page with videos from the paper.
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- Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems,
Peter
Stone and Gerhard Weiss, editors.
Association for Computing Machinery
(ACM), May 2006.
A book based on AAMAS 2006
ISBN: 1-59593-303-4
on-line
version from ACM.
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(unavailable)
- Multiagent Traffic Management: An Improved Intersection Control Mechanism.
Kurt
Dresner and Peter Stone.
In The Fourth International Joint Conference
on Autonomous Agents and Multiagent Systems, ACM Press, New York, NY, July 2005.
Some videos
referenced in the paper. The main project page
Extended
version citable as University of Texas at Austin AI lab technical
report number UT-AI-TR-04-315
AAMAS-2005
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- A Polynomial-time Nash Equilibrium Algorithm for Repeated Games.
Michael
L. Littman and Peter Stone.
Decision Support Systems, 39:55–66
, 2005.
An earlier version appeared in the proceedings of the
fourth annual ACM Conference on Electronic Commerce
Official version from Decision
Support Systems
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- Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism.
Kurt
Dresner and Peter Stone.
In The Third International Joint Conference
on Autonomous Agents and Multiagent Systems, pp. 530–537, July 2004.
Some simulations
of cars driving through intersections referenced in the paper. The main project
page
AAMAS-2004
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- The RoboCup Soccer Server and CMUnited Clients: Implemented Infrastructure for MAS Research.
Itsuki
Noda and Peter Stone.
Autonomous Agents and Multi-Agent Systems,
7(1--2):101–120, July--September 2003.
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- Multiagent Competitions and Research: Lessons from RoboCup and TAC.
Peter
Stone.
In Gal A. Kaminka, Pedro U. Lima, and Raul Rojas, editors,
RoboCup-2002: Robot Soccer World Cup VI, Lecture Notes in Artificial Intelligence, pp. 224–237, Springer Verlag,
Berlin, 2003.
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(216.7kB
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- Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer,
Peter
Stone.
MIT Press, 2000.
A book based on my Ph.D.
thesis
Contents, availability, and on-line appendices
ISBN: 0262194384
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(unavailable)
- Multiagent Systems: A survey from a machine learning perspective.
Peter
Stone and Manuela Veloso.
Autonomous Robots, 8(3):345–383, July
2000.
Formerly citable as Carnegie Mellon University CS technical report number CMU-CS-97-193. December,
1997.
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(292.1kB
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- Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork.
Peter Stone and Manuela Veloso.
Artificial
Intelligence, 110(2):241–273, June 1999.
HTML
version.
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(209.2kB
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(318.6kB
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Multiagent Systems: Ad Hoc Teamwork
- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
Arrasy
Rahman, Jiaxun Cui, and Peter Stone.
In
AAAI, February 2024.
the conference presentation
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(1.3MB
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[slides.ppt]
(9.2MB
)
[poster.pdf]
(956.2kB
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- N-Agent Ad Hoc Teamwork.
Caroline Wang, Arrasy
Rahman, Ishan Durugkar, Elad
Liebman, and Peter Stone.
In Conference on Neural Information Processing
Systems (NeurIPS), December 2024.
Details
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[pdf]
(1.6MB
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[slides.pdf]
(1.3MB
)
[poster.pdf]
(1.7MB
)
- Quantifying Human Rationality in Ad-hoc Teamwork.
Yair Hanina, Reuth
Mirsky, William Macke, and Peter
Stone.
In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
Details
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(404.2kB
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- A Survey of Ad Hoc Teamwork Research.
Reuth Mirsky, Ignacio
Carlucho, Arrasy Rahman, Eliott Fosong, William
Macke, Mohan Sridharan, Peter
Stone, and Stefano Albrecht.
In Baumeister, Dorothea and Rothe, Jörg, editors,
Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
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(198.8kB
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- Expected Value of Communication for Planning in Ad Hoc Teamwork.
William
Macke, Reuth Mirsky, and Peter
Stone.
In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
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[pdf]
(869.9kB
)
[slides.pdf]
(2.3MB
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[poster.pdf]
(1.8MB
)
- Reasoning about Human Behavior in Ad Hoc Teamwork.
Jennifer Suriadinata, William
Macke, Reuth Mirsky, and Peter
Stone.
In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
Video
Presentation
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(926.2kB
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- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
Ishan
Durugkar, Elad Liebman, and Peter
Stone.
In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
2020.
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- A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
Reuth
Mirsky, William Macke, Andy Wang, Harel
Yedidsion, and Peter Stone.
In Proceedings of the 29th International
Joint Conference on Artificial Intelligence, July 2020.
15-minute
presentation
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[pdf]
(1.2MB
)
[slides.pdf]
(1.4MB
)
- Ad hoc Teamwork with Behavior Switching Agents.
Manish Ravula, Shani Alkobi and Peter
Stone.
In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
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[pdf]
(350.4kB
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- Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems.
Stefano
Albrecht and Peter Stone.
Artificial Intelligence, 258:66–95,
Elsevier, 2018.
Available from the publisher's webpage and
arXiv
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(670.7kB
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- Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial.
Stefano
Albrecht, Somchaya Liemhetcharat, and Peter Stone.
Autonomous Agents
and Multi-Agent Systems, 31(4):765–66, July 2017.
Official version from Publisher's
Webpage
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(304.3kB
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- Reasoning about Hypothetical Agent Behaviours and their Parameters.
Stefano Albrecht
and Peter Stone.
In Proceedings of the 16th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
Available from IFAAMAS
and from ACM
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(608.2kB
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[slides.pdf]
(1.2MB
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- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
Ad Hoc Teamwork Robotics Competition.
Katie Genter, Tim
Laue, and Peter Stone.
Autonomous Agents and Multi-Agent Systems
(JAAMAS), 31(4):790–820, Springer, July 2017.
Official version from Publisher's
Webpage
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- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
Patrick
MacAlpine and Peter Stone.
In Gita Sukthankar and Juan
A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
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(518.7kB
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(2.6MB
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[slides.pdf]
(45.5MB
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- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
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- Ad Hoc Teamwork Behaviors for Influencing a Flock.
Katie Genter and
Peter Stone.
Acta Polytechnica, 56(1), 2016.
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(421.5kB
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(1.6MB
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- Adding Influencing Agents to a Flock.
Katie Genter and Peter
Stone.
In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16),
May 2016.
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[pdf]
(1.2MB
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[ps]
(4.5MB
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[slides.pdf]
(433.7kB
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- Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication.
Jonathan Grizou, Samuel
Barrett, Manuel Lopes, and Peter
Stone.
In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
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(339.0kB
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- Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork.
Samuel
Barrett and Peter Stone.
In Proceedings of the Twenty-Ninth AAAI
Conference on Artificial Intelligence, January 2015.
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[pdf]
(993.2kB
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(2.8MB
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- Determining Placements of Influencing Agents in a Flock.
Katie Genter,
Shun Zhang, and Peter Stone.
In
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
Details
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[pdf]
(426.7kB
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[ps]
(1.4MB
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[slides.pdf]
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- Modeling Uncertainty in Leading Ad Hoc Teams.
Noa Agmon, Samuel
Barrett, and Peter Stone.
In Proc. of 13th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2014.
Details
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[pdf]
(255.6kB
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(1.7MB
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- Communicating with Unknown Teammates.
Samuel Barrett, Noa
Agmon, Noam Hazon, Sarit Kraus,
and Peter Stone.
In Proceedings of the Twenty-First European Conference
on Artificial Intelligence, August 2014.
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[pdf]
(215.9kB
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[ps]
(2.6MB
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[slides.pdf]
(1.4MB
)
- Influencing a Flock via Ad Hoc Teamwork.
Katie Genter and Peter
Stone.
In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
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(358.4kB
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[slides.pdf]
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- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
Patrick
MacAlpine, Katie Genter, Samuel
Barrett, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS), September 2014.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
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(4.0MB
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[slides.pdf]
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- Teamwork with Limited Knowledge of Teammates.
Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
In Proceedings of the Twenty-Seventh AAAI Conference on
Artificial Intelligence, July 2013.
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[pdf]
(190.1kB
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[ps]
(2.0MB
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- Cooperating with a Markovian Ad Hoc Teammate.
Doran
Chakraborty and Peter Stone.
In Proceedings of the 12th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
Details
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[pdf]
(202.3kB
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[ps]
(408.2kB
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- Role-Based Ad Hoc Teamwork.
Katie Genter, Noa
Agmon, and Peter Stone.
In Gita Sukthankar, Robert P. Goldman, Christopher
Geib, David V. Pyhadath, and Hung Hai Bui, editors, Plan, Activity, and Intent Recognition: Theory and Practice, pp.
251–272, Elsevier, Philadelphia, PA, USA, 2013.
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- Ad Hoc Teamwork for Leading a Flock.
Katie Genter, Noa
Agmon, and Peter Stone.
In Proceedings of the 12th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.
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(246.7kB
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[ps]
(563.3kB
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[slides.pdf]
(28.3MB
)
- Improving Efficiency of Leading a Flock in Ad Hoc Teamwork Settings.
Katie
Genter, Noa Agmon, and Peter Stone.
In
AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop, May 2013.
Details
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[pdf]
(179.8kB
)
[ps]
(413.8kB
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[slides.pdf]
(13.0MB
)
- Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.
Peter
Stone, Gal A. Kaminka, Sarit
Kraus, Jeffrey S. Rosenschein, and Noa
Agmon.
Artificial Intelligence, 203:35–65, Elsevier, October 2013.
Official
version from journal website.
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(499.6kB
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(734.2kB
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- Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates.
Noa
Agmon and Peter Stone.
In Proc. of 11th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), June 2012.
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(229.4kB
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(757.7kB
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- An Analysis Framework for Ad Hoc Teamwork Tasks.
Samuel Barrett
and Peter Stone.
In Proceedings of the 11th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
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[pdf]
(177.6kB
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[ps]
(1.1MB
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[slides.pdf]
(1.6MB
)
- Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain.
Samuel
Barrett, Peter Stone, and Sarit
Kraus.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
Details
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[pdf]
(361.8kB
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(11.4MB
)
[slides.pdf]
(616.4kB
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- Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
Samuel
Barrett and Peter Stone.
In Tenth International Conference on Autonomous
Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
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(136.1kB
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[ps]
(384.8kB
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- Leading a Best-Response Teammate in an Ad Hoc Team.
Peter Stone,
Gal A. Kaminka, and Jeffrey S. Rosenschein.
In
Esther David, Enrico Gerding, David Sarne, and Onn
Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
pp. 132–146, Springer Verlag, November 2010.
Official version from publisher's
webpage
Details
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[pdf]
(179.3kB
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[ps]
(226.4kB
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- Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination.
Peter
Stone, Gal A. Kaminka, Sarit
Kraus, and Jeffrey S. Rosenschein .
In Proceedings of the Twenty-Fourth
Conference on Artificial Intelligence, July 2010.
AAAI
2010
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[pdf]
(119.0kB
)
[ps]
(266.6kB
)
[slides.pdf]
(8.1MB
)
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
Peter
Stone and Sarit Kraus.
In The Ninth International Conference on Autonomous
Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
supplemental material cited in the paper,
including a proof and an algorithm.
AAMAS 2010
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(180.6kB
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[ps]
(285.3kB
)
Multiagent Systems: Agent Modeling
- N-Agent Ad Hoc Teamwork.
Caroline Wang, Arrasy
Rahman, Ishan Durugkar, Elad
Liebman, and Peter Stone.
In Conference on Neural Information Processing
Systems (NeurIPS), December 2024.
Details
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[pdf]
(1.6MB
)
[slides.pdf]
(1.3MB
)
[poster.pdf]
(1.7MB
)
- Program Embeddings for Rapid Mechanism Evaluation.
Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
and Peter Stone.
In ICRA Workshop on Multi-Robot Learning, May 2023.
Details
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(1.3MB
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[poster.pdf]
(916.2kB
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- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
Roberto Capobianco, Varun Kompella, James
Ault, Guni Sharon, Stacy
Jong, Spencer Fox, Lauren
Meyers, Peter R. Wurman, and Peter
Stone.
The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
Contains
material that was previously published in an AAMAS
2021 paper and a AAAI 2020 Fall
Symposium paper.
Article available from JAIR website.
Simulator
source code.
Details
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[pdf]
(1.6MB
)
- Ad hoc Teamwork with Behavior Switching Agents.
Manish Ravula, Shani Alkobi and Peter
Stone.
In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
Details
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[pdf]
(350.4kB
)
- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
Details
BibTeX
Download:
[pdf]
(917.9kB
)
- Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork.
Samuel
Barrett and Peter Stone.
In Proceedings of the Twenty-Ninth AAAI
Conference on Artificial Intelligence, January 2015.
Details
BibTeX
Download:
[pdf]
(993.2kB
)
[ps]
(2.8MB
)
- Modeling Uncertainty in Leading Ad Hoc Teams.
Noa Agmon, Samuel
Barrett, and Peter Stone.
In Proc. of 13th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2014.
Details
BibTeX
Download:
[pdf]
(255.6kB
)
[ps]
(1.7MB
)
- Communicating with Unknown Teammates.
Samuel Barrett, Noa
Agmon, Noam Hazon, Sarit Kraus,
and Peter Stone.
In Proceedings of the Twenty-First European Conference
on Artificial Intelligence, August 2014.
Details
BibTeX
Download:
[pdf]
(215.9kB
)
[ps]
(2.6MB
)
[slides.pdf]
(1.4MB
)
- Teamwork with Limited Knowledge of Teammates.
Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
In Proceedings of the Twenty-Seventh AAAI Conference on
Artificial Intelligence, July 2013.
Details
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[pdf]
(190.1kB
)
[ps]
(2.0MB
)
- Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain.
Samuel
Barrett, Peter Stone, and Sarit
Kraus.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
Details
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[pdf]
(361.8kB
)
[ps]
(11.4MB
)
[slides.pdf]
(616.4kB
)
- Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree.
Doran
Chakraborty and Peter Stone.
In Proceedings of the Twenty Eighth
International Conference on Machine Learning (ICML), 2011.
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[pdf]
(223.3kB
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[ps]
(521.1kB
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- Convergence, Targeted Optimality and Safety in Multiagent Learning.
Doran
Chakraborty and Peter Stone.
In Proceedings of the Twenty-seventh
International Conference on Machine Learning (ICML), June 2010.
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[pdf]
(196.9kB
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[ps]
(474.1kB
)
- Leading a Best-Response Teammate in an Ad Hoc Team.
Peter Stone,
Gal A. Kaminka, and Jeffrey S. Rosenschein.
In
Esther David, Enrico Gerding, David Sarne, and Onn
Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
pp. 132–146, Springer Verlag, November 2010.
Official version from publisher's
webpage
Details
BibTeX
Download:
[pdf]
(179.3kB
)
[ps]
(226.4kB
)
- Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination.
Peter
Stone, Gal A. Kaminka, Sarit
Kraus, and Jeffrey S. Rosenschein .
In Proceedings of the Twenty-Fourth
Conference on Artificial Intelligence, July 2010.
AAAI
2010
Details
BibTeX
Download:
[pdf]
(119.0kB
)
[ps]
(266.6kB
)
[slides.pdf]
(8.1MB
)
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
Peter
Stone and Sarit Kraus.
In The Ninth International Conference on Autonomous
Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
supplemental material cited in the paper,
including a proof and an algorithm.
AAMAS 2010
Details
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[pdf]
(180.6kB
)
[ps]
(285.3kB
)
- Know Thine Enemy: A Champion RoboCup Coach Agent.
Gregory Kuhlmann,
William B. Knox, and Peter Stone.
In
Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1463–68, July 2006.
AAAI 2006
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(126.0kB
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- The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach.
Gregory
Kuhlmann, Peter Stone, and Justin Lallinger.
In Daniele
Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
in Artificial Intelligence, pp. 636–644, Springer Verlag, Berlin, 2005.
Official version from Publisher's
Webpage© Springer-Verlag
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(112.7kB
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- Defining and Using Ideal Teammate and Opponent Models.
Peter Stone,
Patrick Riley, and Manuela Veloso.
In
Proceedings of the Twelfth Annual Conference on Innovative Applications of Artificial Intelligence, 2000.
AAAI Homepage
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(90.3kB
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Multiagent Systems: Social Agents
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
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- Exploring the Cost of Interruptions in Human-Robot Teaming.
Swathi Mannem, William
Macke, Peter Stone, and Reuth
Mirsky.
In IEEE-RAS Humanoids, December 2023.
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(921.5kB
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[poster.pdf]
(294.3kB
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- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
Reuth
Mirsky and Peter Stone.
In ICSR workshop on Adaptive Social Interaction
and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
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- The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care.
Reuth
Mirsky and Peter Stone.
In Proceedings of the 20th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
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- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
Justin Hart,
Reuth Mirsky, Xuesu Xiao,
Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
Stone.
In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
Video presentation
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(3.2MB
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- Ad hoc Teamwork with Behavior Switching Agents.
Manish Ravula, Shani Alkobi and Peter
Stone.
In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
Details
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[pdf]
(350.4kB
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- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
Harel
Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
Stone, and Raymond Mooney.
In International Conference on Social
Robotics (ICSR), pp. 133–143, November 2019.
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- Decision mechanisms underlying mood-congruent emotional classification.
Corey
N. White, Elad Liebman, and Peter
Stone.
Cognition and Emotion, 32(2):249–58, Taylor \& Francis, 2017.
Available from publisher's
website.
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- Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
W. Bradley Knox and Peter Stone.
Artificial
Intelligence, 225(), August 2015.
Artificial
Intelligence
Contains material that was previously published in a IUI 2013 paper and a RoMan 2012 paper that was nominated as a CoTeSys Cognitive Robotics BEST PAPER AWARD FINALIST.
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- Training a Robot via Human Feedback: A Case Study.
W. Bradley Knox, Peter
Stone, and Cynthia Breazeal.
In International Conference on
Social Robotics, October 2013.
BEST PAPER AWARD WINNER at ICSR 2013
An
associated video summarizing the paper (direct
link).
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- How Humans Teach Agents: A New Experimental Perspective.
W. Bradley Knox,
Brian D. Glass, Bradley
C. Love, W. Todd Maddox, and Peter
Stone.
International Journal of Social Robotics, 4:409–421, Springer Netherlands, October 2012. 10.1007/s12369-012-0163-x
International Journal of Social Robotics
Download article from publisher
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- The Nature of Belief-Directed Exploratory Choice in Human Decision-Making.
W.
Bradley Knox, A. Ross Otto, Peter
Stone, and Bradley Love.
Frontiers in Psychology, 2(398), January 2012.
Frontiers in Psychology
Download
article from publisher (free)
A follow-up
commentary by Erica Yu.
Details
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(unavailable)
- Reinforcement Learning from Simultaneous Human and MDP Reward.
W. Bradley Knox
and Peter Stone.
In Proceedings of the 11th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
AAMAS 2012
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(929.6kB
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(4.9MB
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- Comparing Agents: Success against People in Security Domains.
Raz Lin,
Sarit Kraus, Noa Agmon, Samuel
Barrett, and Peter Stone.
In Proceedings of the Twenty-Fifth AAAI
Conference on Artificial Intelligence, August 2011.
Details
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[pdf]
(387.5kB
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- MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training.
Adam
Setapen, Michael Quinlan, and Peter
Stone.
In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively
from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
supplemental
video cited in the paper.
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[pdf]
(533.2kB
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[ps]
(9.7MB
)
- Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting.
Juhyun
Lee, W. Bradley Knox, and Peter
Stone.
Journal of Physical Agents, 2(2):41–50, July 2008. Special Issue on Human Interaction with Domestic
Robots
Available from journal's web page.
Details
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[pdf]
(2.4MB
)
[ps]
(3.4MB
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- Cobot in LambdaMOO: An Adaptive Social Statistics Agent.
Charles
Lee Isbell, Jr., Michael
Kearns, Satinder Singh, Christian
Shelton, Peter Stone, and Dave
Kormann.
Autonomous Agents and Multiagent Systems, 13(3), November 2006.
JAAMAS
Official
version from publisher's website.
Contains material
that was previously published in an Agents-2001 paper
that won the BEST PAPER AWARD.
Details
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Download:
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Planning
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
Details
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[pdf]
(4.3MB
)
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
Details
BibTeX
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[pdf]
(2.0MB
)
- Dobby: A Conversational Service Robot Driven by GPT-4.
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
Hart.
In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
Details
BibTeX
Download:
[pdf]
(863.8kB
)
[poster.pdf]
(892.0kB
)
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
Yoonchang
Sung, Rahul Shome, and Peter Stone.
In IEEE International Conference
on Robotics and Automation (ICRA), March 2024.
Video
presentation
Details
BibTeX
Download:
[pdf]
(482.7kB
)
- A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo.
Miguel Vasco, Takuma
Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, and Peter
Stone.
In Reinforcement Learning Conference (RLC), August 2024.
arXiv
version
Details
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[pdf]
(15.4MB
)
- Real-time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing.
Catherine Weaver, Roberto
Capobianco, Peter Wurman, Peter Stone,
and Masayoshi Tomizuka.
In American Control Conference (ACC), July 2024.
Project
page with video.
Details
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Download:
[pdf]
(1.5MB
)
- iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots.
Shiqi
Zhang, Piyush Khandelwal, and Peter
Stone.
Robotics and Autonomous Systems, 2024.
Details
BibTeX
Download:
[pdf]
(2.0MB
)
- Task Phasing: Automated Curriculum Learning from Demonstrations.
Vaibhav Bajaj, Guni
Sharon, and Peter Stone.
In Proceedings of the 33rd International
Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
Accompanying code
Details
BibTeX
Download:
[pdf]
(416.0kB
)
- Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search.
Yoonchang
Sung and Peter Stone.
In Robotics: Science and Systems (RSS2023),
July 2023.
Video presentation
Details
BibTeX
Download:
[pdf]
(6.9MB
)
[slides.pdf]
(8.1MB
)
[poster.pdf]
(6.9MB
)
- Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 2nd BARN Challenge at ICRA 2023.
Xuesu Xiao, Zifan Xu, Garrett
Warnell, Peter Stone, Ferran Bebelli Guinjoan, Romulo T. Rodrigues, Herman
Bryunickx, Hanjaya Mandala, Guilherme Christmann, Jose Luis Blanco-Claraco, and and Shravan Somashekara Rai.
IEEE Robotics
\& Automation Magazine, 2023.
Details
BibTeX
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[pdf]
(6.5MB
)
- DynaBARN: Benchmarking Metric Ground Navigation in Dynamic Environments.
Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, and Peter Stone.
In Proceedings of the 2022 IEEE International Symposium on
Safety, Security, and Rescue Robotics (SSRR), November 2022.
Details
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[pdf]
(895.8kB
)
- Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning.
Yoonchang
Sung, Zizhao Wang, and Peter Stone.
In
Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
Details
BibTeX
Download:
[pdf]
(742.0kB
)
[poster.pdf]
(5.7MB
)
- APPL: Adaptive Planner Parameter Learning.
Xuesu Xiao, Zizhao
Wang, Zifan Xu, Bo Liu, abd Gauraang
Dhamankar, Anirudh Nair, Garrett Warnell, and Peter
Stone.
Robotics and Autonomous Systems, May 2022.
Details
BibTeX
Download:
[pdf]
(2.6MB
)
- Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
Autonomous Robots, 46:569–97,
March 2022.
Details
BibTeX
Download:
[pdf]
(1.3MB
)
- Expected Value of Communication for Planning in Ad Hoc Teamwork.
William
Macke, Reuth Mirsky, and Peter
Stone.
In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
Details
BibTeX
Download:
[pdf]
(869.9kB
)
[slides.pdf]
(2.3MB
)
[poster.pdf]
(1.8MB
)
- Reasoning about Human Behavior in Ad Hoc Teamwork.
Jennifer Suriadinata, William
Macke, Reuth Mirsky, and Peter
Stone.
In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
Video
Presentation
Details
BibTeX
Download:
[pdf]
(926.2kB
)
- Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain.
Xuesu
Xiao, Joydeep Biswas, and Peter Stone.
IEEE
Robotics and Automation Letters (RA-L), July 2021.
Contains material that was previously presented in an ICRA21
workshop paper Video
Details
BibTeX
Download:
[pdf]
(3.2MB
)
[slides.pdf]
(23.2MB
)
- Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
IEEE Robotics and Automation Letters (RA-L),
January 2021.
5-minute video demonstration
Project
webpage
Details
BibTeX
Download:
[pdf]
(3.2MB
)
- Agile Robot Navigation through Hallucinated Learning and Sober Deployment.
Xuesu
Xiao, Bo Liu, and Peter Stone.
In
Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
Video
Details
BibTeX
Download:
[pdf]
(3.1MB
)
- A Scavenger Hunt for Service Robots.
Harel Yedidsion,
Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
Stone.
In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
Video presentation
Details
BibTeX
Download:
[pdf]
(1.5MB
)
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
Shih-Yun Lo, Shiqi
Zhang, and Peter Stone.
The Journal of Artificial Intelligence Research
(JAIR), 67, October 2020.
Contains material that was previously published in an AAMAS-18
paper (awarded the Best Robotics Paper Award at AAMAS 2018)
Also
available from JAIR website
Details
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Download:
[pdf]
(4.0MB
)
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
Keting Lu, Shiqi
Zhang, Peter Stone, and Xiaoping
Chen.
In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
Official version from ACL
Digital Library, including a link to the conference presentation
Details
BibTeX
Download:
[pdf]
(3.6MB
)
- Benchmarking Metric Ground Navigation.
Daniel Perille, Abigail Truong, Xuesu
Xiao, and Peter Stone.
In Proceedings of the 2020 IEEE International
Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2020.
Video
presentation
Details
BibTeX
Download:
[pdf]
(2.1MB
)
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, Jonathan Fink, and Peter Stone.
IEEE Robotics and Automation
Letters (RA-L), June 2020.
Presented at International Conference on Intelligent Robots and Systems ({IROS})\\
5-minute Video presentation; 15-minute
Video presentation
Project webpage
Details
BibTeX
Download:
[pdf]
(2.2MB
)
[slides.pdf]
(21.1MB
)
- Ad hoc Teamwork with Behavior Switching Agents.
Manish Ravula, Shani Alkobi and Peter
Stone.
In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
Details
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[pdf]
(350.4kB
)
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
Yuqian
Jiang, Shiqi Zhang, Piyush
Khandelwal, and Peter Stone.
Frontiers of Information Technology
and Electronic Engineering, 20(3):363–373, Springer, March 2019.
Official version from Publisher's
Webpage
Details
BibTeX
Download:
[pdf]
(412.1kB
)
- Multi-Robot Planning with Conflicts and Synergies.
Yuqian Jiang, Harel
Yedidsion, Shiqi Zhang, Guni
Sharon, and Peter Stone.
Autonomous Robots, Springer, March 2019.
Official version from Publisher's Webpage
Details
BibTeX
Download:
[pdf]
(2.0MB
)
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
Yuqian
Jiang, Fangkai Yang, Shiqi
Zhang, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
Details
BibTeX
Download:
[pdf]
(925.2kB
)
- Desiderata for Planning Systems in General-Purpose Service Robots.
Nick Walker,
Yuqian Jiang, Maya Cakmak, and
Peter Stone.
In Proceedings of the ICAPS Workshop on Planning and Robotics
(PlanRob 2019), July 2019.
Details
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[pdf]
(651.5kB
)
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
Harel
Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
Stone, and Raymond Mooney.
In International Conference on Social
Robotics (ICSR), pp. 133–143, November 2019.
Details
BibTeX
Download:
[pdf]
(958.6kB
)
- State Aggregation through Reasoning in Answer Set Programming.
Ginevra Gaudioso, Matteo
Leonetti, and Peter Stone.
In Proceedings of the IJCAI Workshop on
Autonomous Mobile Service Robots (WSR 16), July 2016.
Details
BibTeX
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[pdf]
(776.6kB
)
- A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
Matteo
Leonetti, Luca Iocchi, and Peter Stone.
Artificial Intelligence,
241:103 – 130, September 2016.
Details
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[pdf]
(3.2MB
)
- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
Daniel
Urieli and Peter Stone.
In Proceedings of the 15th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
Details
BibTeX
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[pdf]
(11.9MB
)
- Planning in Action Language $\cal BC$ while Learning Action Costs for Mobile Robots.
Piyush
Khandelwal, Fangkai Yang, Matteo
Leonetti, Vladimir Lifschitz, and Peter
Stone.
In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
Details
BibTeX
Download:
[pdf]
(2.5MB
)
[ps]
(6.0MB
)
- Multi-robot Human Guidance using Topological Graphs.
Piyush Khandelwal
and Peter Stone.
In AAAI Spring 2014 Symposium on Qualitative Representations
for Robots (AAAI-SSS), March 2014.
Details
BibTeX
Download:
[pdf]
(1.1MB
)
[ps]
(7.6MB
)
- Planning in Answer Set Programming while Learning Action Costs for Mobile Robots.
Fangkai
Yang, Piyush Khandelwal, Matteo
Leonetti, and Peter Stone.
In AAAI Spring 2014 Symposium on Knowledge
Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
Details
BibTeX
Download:
[pdf]
(643.4kB
)
[ps]
(5.3MB
)
- Training a Robot via Human Feedback: A Case Study.
W. Bradley Knox, Peter
Stone, and Cynthia Breazeal.
In International Conference on
Social Robotics, October 2013.
BEST PAPER AWARD WINNER at ICSR 2013
An
associated video summarizing the paper (direct
link).
Details
BibTeX
Download:
[pdf]
(2.3MB
)
- A Learning Agent for Heat-Pump Thermostat Control.
Daniel Urieli
and Peter Stone.
In Proceedings of the 12th International Conference
on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
Details
BibTeX
Download:
[pdf]
(426.6kB
)
[slides.pdf]
(4.6MB
)
- Instance-Based Action Models for Fast Action Planning.
Mazda
Ahmadi and Peter Stone.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi,
and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp.
1–16, Springer Verlag, Berlin, 2008.
BEST PAPER AWARD WINNER at RoboCup International Symposium.
Official
version from Publisher's Webpage© Springer-Verlag
Details
BibTeX
Download:
[pdf]
(466.3kB
)
[ps]
(3.0MB
)
- Transferring Instances for Model-Based Reinforcement Learning.
Matthew E. Taylor,
Nicholas K. Jong, and Peter
Stone.
In Machine Learning and Knowledge Discovery in Databases, pp. 488–505, September 2008.
Official
version from Publisher's Webpage© Springer-Verlag
Details
BibTeX
Download:
[pdf]
(304.9kB
)
[ps]
(860.1kB
)
- Predictive Planning for Supply Chain Management.
David Pardoe and
Peter Stone.
In Proceedings of the International Conference on Automated
Planning and Scheduling, June 2006.
ICAPS 2006
Details
BibTeX
Download:
[pdf]
(366.2kB
)
[ps]
(950.9kB
)
- An Architecture for Action Selection in Robotic Soccer.
Peter Stone
and David McAllester.
In Proceedings of the Fifth International
Conference on Autonomous Agents, pp. 316–323, ACM Press, New York, NY, 2001.
Agents-2001
Details
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Download:
[pdf]
(177.5kB
)
[ps]
(174.3kB
)
- Interactive, Repair-Based Planning and Scheduling for Shuttle Payload Operations.
Gregg Rabideau, Steve
Chien, Peter Stone, Jason Willis, Curt Eggemeyer, and Tobias Mann.
In
Proceedings of the 1997 IEEE Aerospace Conference, pp. 325–341, Aspen, CO, February 1997.
Part
1 (pdf version) Part
2 (pdf version) Part
3 (pdf version) Part
4 (pdf version)
Details
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Download:
(unavailable)
- User-guided Interleaving of Planning and Execution.
Peter Stone and
Manuela Veloso.
In M. Ghallab and A. Milani, editors, New Directions
in AI Planning, pp. 103–112, IOS Press, 1996.
Details
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[pdf]
(154.0kB
)
[ps]
(170.7kB
)
- Using Testing to Iteratively Improve Training.
Peter Stone and Manuela Veloso.
In Working Notes of the AAAI 1995 Fall Symposium on Active
Learning, pp. 110–111, Boston, MA, November 1995.
Details
BibTeX
Download:
[pdf]
(18.6kB
)
[ps]
(24.3kB
)
- FLECS: Planning with a Flexible Commitment Strategy.
Manuela Veloso and
Peter Stone.
Journal of Artificial Intelligence Research, 3:25–52,
June 1995.
Available from journal's web page.
Details
BibTeX
Download:
[pdf] [ps]
- The need for different domain-independent heuristics.
Peter Stone,
Manuela Veloso, and Jim Blythe.
In Proceedings
of the Second International Conference on AI Planning Systems, pp. 164–169, June 1994.
Details
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[pdf]
(146.6kB
)
[ps]
(125.5kB
)
- Learning to Solve Complex Planning Problems: Finding Useful Auxiliary Problems.
Peter
Stone and Manuela Veloso.
In Technical Report of the AAAI 1994 Fall Symposium
on Planning and Learning: On to Real Applications, pp. 137–141, New Orleans, LA, November 1994.
Details
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[pdf]
(52.6kB
)
[ps]
(56.8kB
)
Robotics
- Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning.
Caleb Chuck, Carl Qi, Michael
J. Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan
Mehta, Anthony Wang, Peter Stone, Amy Zhang, and Scott
Niekum.
In ICRA Workshop on Manipulation Skills, May 2024.
Details
BibTeX
Download:
[pdf]
(19.7MB
)
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
Shivin Dass, Jiaheng
Hu, Ben Abbatematteo, Peter Stone, and Roberto MartÃn-MartÃn.
In Conference
on Robot Learning (CoRL), November 2024.
Details
BibTeX
Download:
[pdf]
(6.8MB
)
- Telemoma: A Modular and Versatile Teleoperation System for Mobile Manipulation.
Shivin Dass, Wensi Ai, Yuqian
Jiang, Samik Singh, Jiaheng Hu,
Ruohan Zhang, Peter Stone,
Ben Abbatematteo, and Roberto Martin-Martin.
In ICRA Workshop on Mobile Manipulation and Embodied Intelligence,
May 2024.
Details
BibTeX
Download:
[pdf]
(2.9MB
)
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
Details
BibTeX
Download:
[pdf]
(4.3MB
)
- Conflict Avoidance in Social Navigation --- a Survey.
Reuth
Mirsky, Xuesu Xiao, Justin Hart, and
Peter Stone.
ACM Transactions on Human-Robot Interaction, 2024.
Details
BibTeX
Download:
[pdf]
(2.1MB
)
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
Details
BibTeX
Download:
[pdf]
(2.0MB
)
- Dobby: A Conversational Service Robot Driven by GPT-4.
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
Hart.
In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
Details
BibTeX
Download:
[pdf]
(863.8kB
)
[poster.pdf]
(892.0kB
)
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
Yoonchang
Sung, Rahul Shome, and Peter Stone.
In IEEE International Conference
on Robotics and Automation (ICRA), March 2024.
Video
presentation
Details
BibTeX
Download:
[pdf]
(482.7kB
)
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
Zizhao
Wang, Caroline Wang, Xuesu
Xiao, Yuke Zhu, and Peter Stone.
In
AAAI Conference on Artificial Intelligence, February 2024.
Details
BibTeX
Download:
[pdf]
(4.5MB
)
- Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Third BARN Challenge at ICRA 2024 [Competitions].
Xuesu Xiao, Zifan Xu, Aniket Datar, Garrett Warnell, Peter
Stone, Joshua Julian Damanik, Jaewon Jung, Chala Adane Deresa, Than
Duc Huy, Chen Jinyu, Chen Yichen, Joshua Adrian Cahyono, Jingda Wu, Longfei Mo, Mingyang Lv, Bowen Lan, Qingyang Meng, Weizhi
Tao, and Li Cheng.
IEEE Robotics \& Automation Magazine, 2024.
Details
BibTeX
Download:
[pdf]
(1.7MB
)
- iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots.
Shiqi
Zhang, Piyush Khandelwal, and Peter
Stone.
Robotics and Autonomous Systems, 2024.
Details
BibTeX
Download:
[pdf]
(2.0MB
)
- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
Bo
Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
Zhu, and Peter Stone.
In 37th Conference on Neural Information Processing
Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
Details
BibTeX
Download:
[pdf]
(37.6MB
)
[poster.pdf]
(2.6MB
)
- Exploring the Cost of Interruptions in Human-Robot Teaming.
Swathi Mannem, William
Macke, Peter Stone, and Reuth
Mirsky.
In IEEE-RAS Humanoids, December 2023.
Details
BibTeX
Download:
[pdf]
(921.5kB
)
[poster.pdf]
(294.3kB
)
- Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search.
Yoonchang
Sung and Peter Stone.
In Robotics: Science and Systems (RSS2023),
July 2023.
Video presentation
Details
BibTeX
Download:
[pdf]
(6.9MB
)
[slides.pdf]
(8.1MB
)
[poster.pdf]
(6.9MB
)
- Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 2nd BARN Challenge at ICRA 2023.
Xuesu Xiao, Zifan Xu, Garrett
Warnell, Peter Stone, Ferran Bebelli Guinjoan, Romulo T. Rodrigues, Herman
Bryunickx, Hanjaya Mandala, Guilherme Christmann, Jose Luis Blanco-Claraco, and and Shravan Somashekara Rai.
IEEE Robotics
\& Automation Magazine, 2023.
Details
BibTeX
Download:
[pdf]
(6.5MB
)
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
Xiaohan Zhang, Saeid Amiri,
Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
Autonomous
Robots, March 2023.
Official version
on publisher's website
Details
BibTeX
Download:
[pdf]
(2.6MB
)
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
Yifeng
Zhu, Zhenyu Jiang, Peter Stone, and Yuke
Zhu.
In Conference on Robot Learning (CoRL), November 2023.
Details
BibTeX
Download:
[pdf]
(7.3MB
)
[poster.pdf]
(5.2MB
)
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
Eddy Hudson, Garrett
Warnell, Faraz Torabi, and Peter
Stone.
In International Conference on Robotics and Automation (ICRA), May 2022.
Presentation
Video
Details
BibTeX
Download:
[pdf]
(2.5MB
)
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
Details
BibTeX
Download:
[pdf]
(4.2MB
)
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
Haresh
Karnan, Garrett Warnell, Xuesu
Xiao, and Peter Stone.
In International Conference on Robotics and
Automation, 2022, May 2022.
Poster,
Video
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[pdf]
(1.5MB
)
- Adversarial Imitation Learning from Video using a State Observer.
Haresh
Karnan, Garrett Warnell, Faraz
Torabi, and Peter Stone.
In International Conference on Robotics
and Automation, 2022, May 2022.
Video
Details
BibTeX
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[pdf]
(933.2kB
)
- DynaBARN: Benchmarking Metric Ground Navigation in Dynamic Environments.
Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, and Peter Stone.
In Proceedings of the 2022 IEEE International Symposium on
Safety, Security, and Rescue Robotics (SSRR), November 2022.
Details
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[pdf]
(895.8kB
)
- Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning.
Yoonchang
Sung, Zizhao Wang, and Peter Stone.
In
Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
Details
BibTeX
Download:
[pdf]
(742.0kB
)
[poster.pdf]
(5.7MB
)
- APPL: Adaptive Planner Parameter Learning.
Xuesu Xiao, Zizhao
Wang, Zifan Xu, Bo Liu, abd Gauraang
Dhamankar, Anirudh Nair, Garrett Warnell, and Peter
Stone.
Robotics and Autonomous Systems, May 2022.
Details
BibTeX
Download:
[pdf]
(2.6MB
)
- Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
Autonomous Robots, 46:569–97,
March 2022.
Details
BibTeX
Download:
[pdf]
(1.3MB
)
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
Yifeng
Zhu, Peter Stone, and Yuke
Zhu.
IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
Project page
Code
Details
BibTeX
Download:
[pdf]
(9.3MB
)
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
Yifeng
Zhu, Abhishek Joshi, Peter Stone, and Yuke
Zhu.
In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
Project page
Code
Details
BibTeX
Download:
[pdf]
(4.4MB
)
- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
Keya
Ghonasgi, Reuth Mirsky, Sanmit
Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
Deshpande.
In International Conference on Intelligent Robots and Systems (IROS), September 2021.
Video
presentation
Details
BibTeX
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[pdf]
(1.6MB
)
- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
Reuth
Mirsky and Peter Stone.
In ICSR workshop on Adaptive Social Interaction
and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
Details
BibTeX
Download:
[pdf]
(194.4kB
)
- Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain.
Xuesu
Xiao, Joydeep Biswas, and Peter Stone.
IEEE
Robotics and Automation Letters (RA-L), July 2021.
Contains material that was previously presented in an ICRA21
workshop paper Video
Details
BibTeX
Download:
[pdf]
(3.2MB
)
[slides.pdf]
(23.2MB
)
- Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
IEEE Robotics and Automation Letters (RA-L),
January 2021.
5-minute video demonstration
Project
webpage
Details
BibTeX
Download:
[pdf]
(3.2MB
)
- Agile Robot Navigation through Hallucinated Learning and Sober Deployment.
Xuesu
Xiao, Bo Liu, and Peter Stone.
In
Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
Video
Details
BibTeX
Download:
[pdf]
(3.1MB
)
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
Siddarth Desai, Ishan
Durugkar, Haresh Karnan, Garrett
Warnell, Josiah Hanna, and Peter
Stone.
In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
December 2020.
Poster
Details
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[pdf]
(1.3MB
)
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Siddharth Desai, Haresh
Karnan, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
11-minute video
presentation.
Details
BibTeX
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[pdf]
(1.9MB
)
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
Haresh
Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
14-minute video
presentation.
Details
BibTeX
Download:
[pdf]
(506.6kB
)
- Benchmarking Metric Ground Navigation.
Daniel Perille, Abigail Truong, Xuesu
Xiao, and Peter Stone.
In Proceedings of the 2020 IEEE International
Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2020.
Video
presentation
Details
BibTeX
Download:
[pdf]
(2.1MB
)
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
Xuesu
Xiao, Bo Liu, Garrett
Warnell, Jonathan Fink, and Peter Stone.
IEEE Robotics and Automation
Letters (RA-L), June 2020.
Presented at International Conference on Intelligent Robots and Systems ({IROS})\\
5-minute Video presentation; 15-minute
Video presentation
Project webpage
Details
BibTeX
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[pdf]
(2.2MB
)
[slides.pdf]
(21.1MB
)
- Ad hoc Teamwork with Behavior Switching Agents.
Manish Ravula, Shani Alkobi and Peter
Stone.
In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
Details
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[pdf]
(350.4kB
)
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
Yuqian
Jiang, Shiqi Zhang, Piyush
Khandelwal, and Peter Stone.
Frontiers of Information Technology
and Electronic Engineering, 20(3):363–373, Springer, March 2019.
Official version from Publisher's
Webpage
Details
BibTeX
Download:
[pdf]
(412.1kB
)
- Multirobot Symbolic Planning under Temporal Uncertainty.
Shiqi Zhang,
Yuqian Jiang, Guni Sharon, and Peter
Stone.
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
May 2017.
Accompanying videos at https://youtu.be/ADbH3sppLHQ
Details
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[pdf]
(2.3MB
)
- Dynamically Constructed (PO)MDPs for Adaptive Robot Planning.
Shiqi
Zhang, Piyush Khandelwal, and Peter
Stone.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
Details
BibTeX
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[pdf]
(3.2MB
)
- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
Details
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[pdf]
(917.9kB
)
- A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
Matteo
Leonetti, Luca Iocchi, and Peter Stone.
Artificial Intelligence,
241:103 – 130, September 2016.
Details
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(3.2MB
)
- Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors.
Jivko
Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone.
In Proceedings
of the 25th International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
Details
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Download:
[pdf]
(6.6MB
)
[slides.pdf]
(5.2MB
)
- Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy.
Jesse Thomason,
Jivko Sinapov, Maxwell Svetlik, Peter
Stone, and Raymond Mooney.
In Proceedings of the 25th international
joint conference on Artificial Intelligence (IJCAI), July 2016.
Demo Video
Details
BibTeX
Download:
[pdf]
(3.1MB
)
[slides.pdf]
(1.0MB
)
- Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy.
Shiqi
Zhang, Fangkai Yang, Piyush
Khandelwal, and Peter Stone.
In Proceedings of the 13th International
Conference on Logic Programming and Non-monotonic Reasoning (LPNMR), September 2015.
Demo Video
Details
BibTeX
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[pdf]
(2.6MB
)
[slides.pdf]
(1.3MB
)
- TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots.
Todd
Hester and Peter Stone.
Machine Learning, 90(3):385–429,
2013.
Official version
from journal website.
Details
BibTeX
Download:
[pdf]
(987.8kB
)
[ps]
(3.2MB
)
- A Platform for Evaluating Autonomous Intersection Management Policies.
Chien-Liang
Fok, Maykel Hanna, Seth Gee, Tsz-Chiu
Au, Peter Stone, Christine
Julien, and Sriram Vishwanath.
In Proceedings
of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.
Details
BibTeX
Download:
[pdf]
(5.7MB
)
[ps]
(61.7MB
)
- RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control.
Todd
Hester, Michael Quinlan, and Peter
Stone.
In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
Details
BibTeX
Download:
[pdf]
(359.7kB
)
[ps]
(1.9MB
)
- Generalized Model Learning for Reinforcement Learning on a Humanoid Robot.
Todd
Hester, Michael Quinlan, and Peter
Stone.
In IEEE International Conference on Robotics and Automation (ICRA), May 2010.
Video available at
http://www.cs.utexas.edu/~AustinVilla/?p=research/rl_kick
Details
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Download:
[pdf]
(1.5MB
)
[ps]
(25.3MB
)
- Improving Particle Filter Performance Using SSE Instructions.
Peter
Djeu, Michael Quinlan, and Peter
Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
2009.
Details
BibTeX
Download:
[pdf]
(176.8kB
)
[ps]
(2.7MB
)
- Connectivity-based Localization in Robot Networks.
Tobias Jung,
Mazda Ahmadi, and Peter
Stone.
In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
Details
BibTeX
Download:
[pdf]
(176.8kB
)
[ps]
(514.7kB
)
- Negative Information and Line Observations for Monte Carlo Localization.
Todd
Hester and Peter Stone.
In IEEE International Conference on Robotics
and Automation, May 2008.
ICRA 2008
Details
BibTeX
Download:
[pdf]
(128.7kB
)
[ps]
(501.7kB
)
- Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents.
Daniel
Stronger and Peter Stone.
International Journal on Artificial Intelligence
Tools, 17(1):159–174, February 2008.
official
published version
Details
BibTeX
Download:
[pdf]
(236.4kB
)
[ps]
(1.0MB
)
- Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot.
Daniel
Stronger and Peter Stone.
In IEEE International Conference on Robotics
and Automation, May 2008.
ICRA 2008
Details
BibTeX
Download:
[pdf]
(182.1kB
)
[ps]
(902.7kB
)
- Learning and Multiagent Reasoning for Autonomous Agents.
Peter Stone.
In
The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
IJCAI-07
Details
BibTeX
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[pdf]
(308.5kB
)
[ps]
(379.3kB
)
- DARPA Urban Challenge Technical Report: Austin Robot Technology.
Peter
Stone, Patrick Beeson, Tekin
Mericli, and Ryan Madigan.
June 2007. Available from http://www.darpa.mil/grandchallenge/rules.asp
Details
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[pdf]
(2.7MB
)
- A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot.
Daniel
Stronger and Peter Stone.
In IEEE International Conference on Robotics
and Automation, pp. 3915–3920, April 2007.
Details
BibTeX
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[pdf]
(271.4kB
)
[ps]
(2.2MB
)
- From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty.
Peter
Stone, Mohan Sridharan, Daniel
Stronger, Gregory Kuhlmann, Nate Kohl,
Peggy Fidelman, and Nicholas
K. Jong.
Robotics and Autonomous Systems , 54(11):933–43, November 2006. Special issue on Planning
Under Uncertainty in Robotics.
Official versionfrom the RAS
publisher's webpage.
Details
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[pdf]
(260.5kB
)
[ps]
(3.6MB
)
- Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot.
Daniel
Stronger and Peter Stone.
Connection Science, 18(2):97–119,
2006. Special Issue on Developmental Robotics.
Connection
Science Journal. Contains material that was previously published in an ICRA-2005
paper.
Details
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[pdf]
(372.6kB
)
[ps]
(1.4MB
)
- Continuous Area Sweeping: A Task Definition and Initial Approach.
Mazda
Ahmadi and Peter Stone.
In The 12th International Conference on Advanced
Robotics, July 2005.
Some videos of
the robot referenced in the paper.
ICAR 2005
Details
BibTeX
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[pdf]
(186.7kB
)
[ps]
(243.1kB
)
- A Model-Based Approach to Robot Joint Control.
Daniel
Stronger and Peter Stone.
In Daniele
Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
in Artificial Intelligence, pp. 297–309, Springer Verlag, Berlin, 2005.
Official version from Publisher's
Webpage© Springer-Verlag
Details
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[pdf]
(235.3kB
)
[ps]
(489.4kB
)
Robotics: Autonomous Driving
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
Haresh,
Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
In
International Conference on Robotics and Automation, May 2024.
Details
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Download:
[pdf]
(4.3MB
)
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
Details
BibTeX
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[pdf]
(2.0MB
)
- A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo.
Miguel Vasco, Takuma
Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, and Peter
Stone.
In Reinforcement Learning Conference (RLC), August 2024.
arXiv
version
Details
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[pdf]
(15.4MB
)
- Real-time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing.
Catherine Weaver, Roberto
Capobianco, Peter Wurman, Peter Stone,
and Masayoshi Tomizuka.
In American Control Conference (ACC), July 2024.
Project
page with video.
Details
BibTeX
Download:
[pdf]
(1.5MB
)
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
Haresh
Karnan, Elvin Yang, Daniel Farkash, Garrett
Warnell, Joydeep Biswas, and Peter
Stone.
In The Conference on Robot Learning (CoRL), November 2023.
Poster,
Video, Project Website
Details
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[pdf]
(25.7MB
)
- Reward (Mis)design for Autonomous Driving.
W. Bradley Knox, Alessandro Allievi,
Holger Banzhaf, Felix Schmitt, and Peter Stone.
Artificial Intelligence,
316:103829, 2023.
Paper webpage
Details
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[pdf]
(696.3kB
)
[ps]
(5.6MB
)
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
Jinsoo Park, Xuesu
Xiao, Garrett Warnell, Harel
Yedidsion, and Peter Stone.
In Proceedings of the 2023 IEEE International
Conference on Robotics and Automation (ICRA 2023), May 2023.
6-minute video
presentation
Details
BibTeX
Download:
[pdf]
(4.6MB
)
[slides.pptx]
(21.3MB
)
[poster.pdf]
(1.1MB
)
- Visually Adaptive Geometric Navigation.
Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
Xiao, Garrett Warnell, Joydeep
Biswas, and Peter Stone.
In IEEE International Symposium on Safety,Security,and
Rescue Robotics, November 2023.
Details
BibTeX
Download:
[pdf]
(4.8MB
)
- Benchmarking Reinforcement Learning Techniques for Autonomous Navigation.
Zifan
Xu, Bo Liu, Xuesu Xiao, Anirudh
Nair, and Peter Stone.
In Proceedings of the 2023 IEEE International
Conference on Robotics and Automation (ICRA 2023), May 2023.
Details
BibTeX
Download:
[pdf]
(4.8MB
)
- Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis.
Zifan
Xu, Anirudh Nair, Xuesu Xiao, and Peter
Stone.
In IROS Workshop on Photorealistic Image and Environment Synthesis for Robotics (PIES-Rob) , January
2023.
Details
BibTeX
Download:
[pdf]
(4.3MB
)
- Learning a robust multiagent driving policy for traffic congestion reduction.
Yulin
Zhang, William Macke, Jiaxun Cui,
Sharon Hornstein, Daniel Urieli, and Peter
Stone.
Neural Computing and Applications, 2023.
Details
BibTeX
Download:
[pdf]
(1.2MB
)
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
Jiaxun
Cui, Hang Qiu, Dian Chen, Peter
Stone, and Yuke Zhu.
In IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), June 2022.
Project website
Details
BibTeX
Download:
[pdf]
(3.5MB
)
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
Details
BibTeX
Download:
[pdf]
(4.2MB
)
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
Haresh
Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
Warnell, Peter Stone, and Joydeep Biswas.
In
International Conference on Intelligent Robots and Systems, 2022, October 2022.
Details
BibTeX
Download:
[pdf]
(3.0MB
)
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
Haresh
Karnan, Garrett Warnell, Xuesu
Xiao, and Peter Stone.
In International Conference on Robotics and
Automation, 2022, May 2022.
Poster,
Video
Details
BibTeX
Download:
[pdf]
(1.5MB
)
- Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning.
Peter
R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik
Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Varun
Kompella, Piyush Khandelwal, HaoChih
Lin, Patrick MacAlpine, Declan Oller, Craig Sherstan, Takuma Seno, Michael
D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead,
Peter Duerr, Peter Stone, Michael Spranger, and and
Hiroaki Kitano.
Nature, 62:223–28, Feb. 2022.
Available from Nature
website.
project webpage
Details
BibTeX
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[pdf]
(2.7MB
)
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
Jiaxun
Cui, William Macke, Harel
Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
Stone.
In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
May 2021.
Project page, with videos
Details
BibTeX
Download:
[pdf]
(1.4MB
)
[slides.pptx]
(1.5MB
)
- A Lifelong Learning Approach to Mobile Robot Navigation.
Bo Liu, Xuesu Xiao, and Peter Stone.
IEEE
Robotics and Automation Letters (RA-L), 6(2), April 2021.
Presented at IEEE International Conference on Robotics
and Automation (ICRA),
Video presentation
Details
BibTeX
Download:
[pdf]
(3.6MB
)
- Team Orienteering Coverage Planning with Uncertain Reward.
Bo Liu,
Xuesu Xiao, and Peter Stone.
In
International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
Details
BibTeX
Download:
[pdf]
(3.9MB
)
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
Zizhao
Wang, Xuesu Xiao, Bo Liu,
Garrett Warnell, and Peter
Stone.
IEEE Robotics and Automation Letters (RA-L), October 2021.
5-minute
Video Presentation; 15-minute Video Presentation
Details
BibTeX
Download:
[pdf]
(1.1MB
)
[slides.pdf]
(2.7MB
)
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
Zizhao
Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
In Proceedings
of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
1-minute
Video Summary; 15-minute Video Presentation
Details
BibTeX
Download:
[pdf]
(2.9MB
)
[slides.pdf]
(2.7MB
)
- APPLI: Adaptive Planner Parameter Learning From Interventions.
Zizhao Wang,
Xuesu Xiao, Bo Liu, Garrett
Warnell, and Peter Stone.
In Proceedings of the International Conference
on Robotics and Automation (ICRA 2021), May 2021.
Video presentation
Details
BibTeX
Download:
[pdf]
(4.2MB
)
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
Zifan Xu,
Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
Warnell, Bo Liu, Zizhao Wang,
and Peter Stone.
In Proceedings of the 2021 IEEE International Conference
on Robotics and Automation (ICRA 2021), June 2021.
Video
presentation
Project webpage
Details
BibTeX
Download:
[pdf]
(3.4MB
)
[slides.pptx]
(27.4MB
)
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
Zifan
Xu, Xuesu Xiao, Garrett
Warnell, Anirudh Nair, and Peter Stone.
In Proceedings of the 2021
IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
Video
presentation
Details
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Download:
[pdf]
(4.5MB
)
- Inferring User Intention using Gaze in Vehicles.
Yu-Sian Jiang, Garrett
Warnell, and Peter Stone.
In The 20th ACM International Conference
on Multimodal Interaction (ICMI), October 2018.
Based on an earlier version presented at the AAAI
PAIR workshop
Details
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[pdf]
(2.6MB
)
- A Study of Human-Robot Copilot Systems for En-Route Destination Changing.
Yu-Sian Jiang, Garrett
Warnell, Eduardo Munera, and Peter Stone.
In Proceedings of the 27th
IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), August 2018.
Available
from RO-MAN
Details
BibTeX
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[pdf]
(5.8MB
)
[slides.pptx]
(32.7MB
)
- Setpoint Scheduling for Autonomous Vehicle Controllers.
Tsz-Chiu Au,
Michael Quinlan, and Peter
Stone.
In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
Details
BibTeX
Download:
[pdf]
(684.9kB
)
[ps]
(2.7MB
)
- A Platform for Evaluating Autonomous Intersection Management Policies.
Chien-Liang
Fok, Maykel Hanna, Seth Gee, Tsz-Chiu
Au, Peter Stone, Christine
Julien, and Sriram Vishwanath.
In Proceedings
of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.
Details
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[pdf]
(5.7MB
)
[ps]
(61.7MB
)
- Bringing Simulation to Life: A Mixed Reality Autonomous Intersection.
Michael
Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter
Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
2010.
Video available at http://www.cs.utexas.edu/~aim/video/MixedReality.wmv
Details
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[pdf]
(1.3MB
)
[ps]
(10.6MB
)
- Multiagent Interactions in Urban Driving.
Patrick Beeson, Jack
O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter
Stone.
Journal of Physical Agents, 2(1):15–30, March 2008. Special issue on Multi-Robot Systems
JoPhA
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Robotics: Quadruped Robots
- Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning.
Zifan
Xu, Amir Hossain Raj, Xuesu Xiao, and Peter
Stone.
In IEEE International Conference on Robotics and Automation, May 2024.
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- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
Elliott
Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
Wang, Justin Hart, Reuth Mirsky,
Joydeep Biswas, Junfeng Jiao, and Peter
Stone.
In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
1–15, July 2023.
Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
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- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
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(4.2MB
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- Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker.
Matthew
Hausknecht and Peter Stone.
In Javier
Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
Video and source code available at
http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
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- MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training.
Adam
Setapen, Michael Quinlan, and Peter
Stone.
In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively
from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
supplemental
video cited in the paper.
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[pdf]
(533.2kB
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[ps]
(9.7MB
)
- Instance-Based Action Models for Fast Action Planning.
Mazda
Ahmadi and Peter Stone.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi,
and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp.
1–16, Springer Verlag, Berlin, 2008.
BEST PAPER AWARD WINNER at RoboCup International Symposium.
Official
version from Publisher's Webpage© Springer-Verlag
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(3.0MB
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- A Neural Network-Based Approach to Robot Motion Control.
Uli Grasemann, Daniel
Stronger, and Peter Stone.
In Ubbo Visser, Fernando Ribeiro, Takeshi
Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence,
pp. 480–87, Springer Verlag, Berlin, 2008.
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(280.9kB
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(1.6MB
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- The Chin Pinch: A Case Study in Skill Learning on a Legged Robot.
Peggy
Fidelman and Peter Stone.
In Gerhard Lakemeyer, Elizabeth
Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
in Artificial Intelligence, pp. 59–71, Springer Verlag, Berlin, 2007.
Some videos
referenced in the paper.
Details
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(186.9kB
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(1.6MB
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- Autonomous Learning of Stable Quadruped Locomotion.
Manish
Saggar, Thomas D'Silva, Nate Kohl, and Peter
Stone.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
98–109, Springer Verlag, Berlin, 2007.
BEST PAPER AWARD NOMINEE at RoboCup International Symposium.
Some videos referenced in the paper.
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[pdf]
(1.1MB
)
[ps]
(26.8MB
)
- Intelligent Autonomous Robotics: A Robot Soccer Case Study,
Peter
Stone.
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
Available from Synthesis page.
ISBN: 9781598291262
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(unavailable)
- Selective Visual Attention for Object Detection on a Legged Robot.
Daniel
Stronger and Peter Stone.
In Gerhard Lakemeyer, Elizabeth
Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
in Artificial Intelligence, pp. 158–170, Springer Verlag, Berlin, 2007.
Some videos
referenced in the paper.
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[pdf]
(159.7kB
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[ps]
(342.4kB
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- The UT Austin Villa 2006 RoboCup Four-Legged Team.
Peter Stone, Peggy Fidelman, Nate Kohl, Gregory
Kuhlmann, Tekin Mericli, Mohan Sridharan,
and Shao-en Yu.
Technical Report UT-AI-TR-06-337, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2006.
At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2006.html#06-337
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[ps]
(127.2kB
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- Practical Vision-Based Monte Carlo Localization on a Legged Robot.
Mohan
Sridharan, Gregory Kuhlmann, and Peter
Stone.
In IEEE International Conference on Robotics and Automation, April 2005.
ICRA
2005
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(217.6kB
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(2.0MB
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- The UT Austin Villa 2005 RoboCup Four-Legged Team.
Peter Stone, Kurt Dresner, Peggy
Fidelman, Nate Kohl, Gregory Kuhlmann,
Mohan Sridharan, and Daniel
Stronger.
Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2005.
At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2005.html#05-325
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[pdf]
(186.2kB
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[ps]
(243.4kB
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- Machine Learning for Fast Quadrupedal Locomotion.
Nate Kohl and Peter
Stone.
In The Nineteenth National Conference on Artificial Intelligence, pp. 611–616, July 2004.
Some videos of walking robots referenced in
the paper.
AAAI 2004
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(210.0kB
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[ps]
(1.4MB
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- Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion.
Nate Kohl
and Peter Stone.
In Proceedings of the IEEE International Conference
on Robotics and Automation, May 2004.
Some videos
of walking robots referenced in the paper.
ICRA 2004
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[pdf]
(301.5kB
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[ps]
(3.2MB
)
- The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age.
Peter
Stone, Kurt Dresner, Peggy
Fidelman, Nicholas K. Jong, Nate
Kohl, Gregory Kuhlmann, Mohan
Sridharan, and Daniel Stronger.
Technical Report
UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2004.html#04-313
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(555.3kB
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(1.6MB
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- The UT Austin Villa 2003 Four-Legged Team.
Peter Stone, Kurt
Dresner, Selim T. Erdo\ugan, Peggy Fidelman, Nicholas
K. Jong, Nate Kohl, Gregory Kuhlmann,
Ellie Lin, Mohan Sridharan, Daniel Stronger, and Gurushyam Hariharan.
In Daniel
Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, RoboCup-2003: Robot Soccer World Cup VII,
Springer Verlag, Berlin, 2004.
Extended
version (technical report with full details: "UT Austin Villa 2003: A New RoboCup Four-Legged Team").
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Robotics: Humanoid Robots
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
Josiah
P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
Warnell, and Peter Stone.
Special Issue on Reinforcement Learning
for Real Life, Machine Learning, 2021, May 2021.
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- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Siddharth Desai, Haresh
Karnan, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
11-minute video
presentation.
Details
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- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
Ad Hoc Teamwork Robotics Competition.
Katie Genter, Tim
Laue, and Peter Stone.
Autonomous Agents and Multi-Agent Systems
(JAAMAS), 31(4):790–820, Springer, July 2017.
Official version from Publisher's
Webpage
Details
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[pdf]
(1.2MB
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- Grounded Action Transformation for Robot Learning in Simulation.
Josiah
Hanna and Peter Stone.
In Proceedings of the 31st AAAI Conference
on Artificial Intelligence (AAAI), February 2017.
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[pdf]
(1.3MB
)
[slides.pdf]
(1.3MB
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- UT Austin Villa RoboCup 3D Simulation Base Code Release.
Patrick MacAlpine
and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
Code release at https://github.com/LARG/utaustinvilla3d
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(394.2kB
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(2.1MB
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[slides.pdf]
(107.1MB
)
- Dynamic Behaviors on the NAO Robot With Closed-Loop Whole Body Operational Space Control.
Donghyun Kim, Steven Jens
Jorgensen, Peter Stone, and Luis
Sentis.
In IEEE-RAS International Conference on Humanoid Robots, 2016.
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[pdf]
(4.0MB
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- A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer.
David
L. Leottau, Javier Ruiz-del-Solar, Patrick
MacAlpine, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
Details
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[pdf]
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- Adaptation of Surrogate Tasks for Bipedal Walk Optimization.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
Details
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[pdf]
(172.1kB
)
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(739.5kB
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[slides.pdf]
(165.0MB
)
- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
Patrick
MacAlpine, Katie Genter, Samuel
Barrett, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS), September 2014.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
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[pdf]
(491.0kB
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(4.0MB
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[slides.pdf]
(30.4MB
)
- The 2012 UT Austin Villa Code Release.
Samuel Barrett, Katie
Genter, Yuchen He, Todd
Hester, Piyush Khandelwal, Jacob
Menashe, and Peter Stone.
In RoboCup-2013: Robot Soccer World Cup
XVII, Springer Verlag, 2013.
Details
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(376.3kB
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(2.1MB
)
- UT Austin Villa 2012: Standard Platform League World Champions.
Samuel
Barrett, Katie Genter, Yuchen
He, Todd Hester, Piyush Khandelwal,
Jacob Menashe, and Peter Stone.
In
Xiaoping Chen, Peter
Stone, Luis Enrique Sucar, and Tijn
Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2013.
Details
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[pdf]
(740.4kB
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[ps]
(15.0MB
)
- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
Alon
Farchy, Samuel Barrett, Patrick
MacAlpine, and Peter Stone.
In Proc. of 12th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2013.
The videos referenced in the paper: original
and optimized.
Details
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[pdf]
(486.2kB
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(36.5MB
)
- UT Austin Villa: RoboCup 2012 3D Simulation League Champion.
Patrick
MacAlpine, Nick Collins, Adrian
Lopez-Mobilia, and Peter Stone.
In Xiaoping
Chen, Peter Stone, Luis Enrique
Sucar, and Tijn Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup
XVI, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/results_3d/#highlights
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(6.7MB
)
- Positioning to Win: A Dynamic Role Assignment and FormationPositioning System.
Patrick
MacAlpine, Francisco Barrera, and Peter
Stone.
In Xiaoping Chen, Peter
Stone, Luis Enrique Sucar, and Tijn
Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2013.
Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/positioning.html
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(255.9kB
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[ps]
(722.6kB
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[slides.pdf]
(44.0MB
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- Simultaneous Learning and Reshaping of an Approximated Optimization Task.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
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[pdf]
(435.1kB
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[ps]
(2.1MB
)
[slides.pdf]
(35.2MB
)
- UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy.
Jacob
Menashe, Katie Genter, Samuel
Barrett, and Peter Stone.
In The Eighth Workshop on Humanoid Soccer
Robots at Humanoids 2013, October 2013.
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[pdf]
(350.2kB
)
[ps]
(24.1MB
)
[slides.pdf]
(3.1MB
)
- Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions.
Aijun
Bai, Xiaoping Chen, Patrick
MacAlpine, Daniel Urieli, Samuel
Barrett, and Peter Stone.
In Thomas Roefer, Norbert Michael Mayer, Jesus
Savage, and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence,
Springer Verlag, Berlin, 2012.
Details
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[pdf]
(257.0kB
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[ps]
(829.5kB
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- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
Samuel
Barrett, Katie Genter, Todd Hester,
Piyush Khandelwal, Michael
Quinlan, Peter Stone, and Mohan
Sridharan.
Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2012.
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[pdf]
(1.1MB
)
[ps]
(32.8MB
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- Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition.
Patrick MacAlpine, Samuel Barrett,
Daniel Urieli, Victor
Vu, and Peter Stone.
In Proceedings of the Twenty-Sixth AAAI Conference
on Artificial Intelligence (AAAI), July 2012.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html
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(2.0MB
)
[slides.pdf]
(204.2MB
)
- UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition.
Patrick
MacAlpine, Daniel Urieli, Samuel
Barrett, Shivaram Kalyanakrishnan, Francisco
Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua,
Victor Vu, and Peter
Stone.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
Accompanying
videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/components.html
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(2.7MB
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[slides.pdf]
(135.4MB
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- Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk.
Patrick
MacAlpine and Peter Stone.
In AAMAS Adaptive Learning Agents (ALA)
Workshop, June 2012.
Video available at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/holonomicwalk.html
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[pdf]
(525.6kB
)
[ps]
(2.2MB
)
[slides.pdf]
(159.5MB
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- Austin Villa 2010 Standard Platform Team Report.
Samuel Barrett,
Katie Genter, Matthew Hausknecht,
Todd Hester, Piyush Khandelwal,
Juhyun Lee, Michael
Quinlan, Aibo Tian, Peter Stone,
and Mohan Sridharan.
Technical Report UT-AI-TR-11-01, The University of Texas
at Austin, Department of Computer Sciences, AI Laboratory, 2011.
Details
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[pdf]
(1.3MB
)
[ps]
(38.0MB
)
- UT Austin Villa 2011 3D Simulation Team Report.
Patrick MacAlpine,
Daniel Urieli, Samuel Barrett,
Shivaram Kalyanakrishnan, Francisco
Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua,
Victor Vu, and Peter
Stone.
Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
2011.
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[pdf]
(1.2MB
)
[ps]
(5.3MB
)
- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
Daniel
Urieli, Patrick MacAlpine, Shivaram
Kalyanakrishnan, Yinon Bentor, and Peter
Stone.
In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
May 2011.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
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[slides.pptx]
(3.8MB
)
- Controlled Kicking under Uncertainty.
Samuel Barrett, Katie
Genter, Todd Hester, Michael
Quinlan, and Peter Stone.
In The Fifth Workshop on Humanoid Soccer
Robots at Humanoids 2010, December 2010.
Details
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[pdf]
(357.3kB
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[ps]
(17.7MB
)
- Transfer Learning for Reinforcement Learning on a Physical Robot.
Samuel
Barrett, Matt E. Taylor, and Peter
Stone.
In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents
Workshop (AAMAS - ALA), May 2010.
AAMAS ALA 2010
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(688.8kB
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(5.7MB
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- Three Humanoid Soccer Platforms: Comparison and Synthesis.
Shivaram
Kalyanakrishnan, Todd Hester, Michael
Quinlan, Yinon Bentor, and Peter
Stone.
In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot
Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
Details
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(379.0kB
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[ps]
(5.3MB
)
- Vision Calibration and Processing on a Humanoid Soccer Robot.
Piyush
Khandelwal, Matthew Hausknecht, Juhyun
Lee, Aibo Tian, and Peter Stone.
In
The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
Details
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(402.6kB
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[ps]
(14.8MB
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- MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training.
Adam
Setapen, Michael Quinlan, and Peter
Stone.
In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively
from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
supplemental
video cited in the paper.
Details
BibTeX
Download:
[pdf]
(533.2kB
)
[ps]
(9.7MB
)
- The Essence of Soccer, Can Robots Play Too?.
Peter Stone, Michael
Quinlan, and Todd Hester.
In Ted Richards, editors, Soccer and Philosophy:
Beautiful Thoughts on theBeautiful Game, Popular Culture and Philosophy, pp. 75–88, Open Court Publishing Company,
2010.
Appears in Soccer and Philosophy (available from amazon.com)
Details
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[pdf]
(121.3kB
)
[ps]
(514.1kB
)
- TT-UT Austin Villa 2009: Naos across Texas.
Todd Hester, Michael
Quinlan, Peter Stone, and Mohan
Sridharan.
Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
2009.
Details
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[pdf]
(787.9kB
)
[ps]
(7.0MB
)
- UT Austin Villa 2008: Standing on Two Legs.
Todd Hester, Michael
Quinlan, and Peter Stone.
Technical Report UT-AI-TR-08-8, The University
of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2008.
Details
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[pdf]
(705.9kB
)
[ps]
(6.2MB
)
Robotics: Real Robot Soccer
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Siddharth Desai, Haresh
Karnan, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
11-minute video
presentation.
Details
BibTeX
Download:
[pdf]
(1.9MB
)
- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
Ad Hoc Teamwork Robotics Competition.
Katie Genter, Tim
Laue, and Peter Stone.
Autonomous Agents and Multi-Agent Systems
(JAAMAS), 31(4):790–820, Springer, July 2017.
Official version from Publisher's
Webpage
Details
BibTeX
Download:
[pdf]
(1.2MB
)
- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
Patrick
MacAlpine, Katie Genter, Samuel
Barrett, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS), September 2014.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
Details
BibTeX
Download:
[pdf]
(491.0kB
)
[ps]
(4.0MB
)
[slides.pdf]
(30.4MB
)
- The 2012 UT Austin Villa Code Release.
Samuel Barrett, Katie
Genter, Yuchen He, Todd
Hester, Piyush Khandelwal, Jacob
Menashe, and Peter Stone.
In RoboCup-2013: Robot Soccer World Cup
XVII, Springer Verlag, 2013.
Details
BibTeX
Download:
[pdf]
(376.3kB
)
[ps]
(2.1MB
)
- UT Austin Villa 2012: Standard Platform League World Champions.
Samuel
Barrett, Katie Genter, Yuchen
He, Todd Hester, Piyush Khandelwal,
Jacob Menashe, and Peter Stone.
In
Xiaoping Chen, Peter
Stone, Luis Enrique Sucar, and Tijn
Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2013.
Details
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Download:
[pdf]
(740.4kB
)
[ps]
(15.0MB
)
- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
Alon
Farchy, Samuel Barrett, Patrick
MacAlpine, and Peter Stone.
In Proc. of 12th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2013.
The videos referenced in the paper: original
and optimized.
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(486.2kB
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(36.5MB
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- UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy.
Jacob
Menashe, Katie Genter, Samuel
Barrett, and Peter Stone.
In The Eighth Workshop on Humanoid Soccer
Robots at Humanoids 2013, October 2013.
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(350.2kB
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[ps]
(24.1MB
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- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
Samuel
Barrett, Katie Genter, Todd Hester,
Piyush Khandelwal, Michael
Quinlan, Peter Stone, and Mohan
Sridharan.
Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2012.
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[pdf]
(1.1MB
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[ps]
(32.8MB
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- A Low Cost Ground Truth Detection System Using the Kinect.
Piyush Khandelwal
and Peter Stone.
In Thomas Roefer, Norbert Michael Mayer, Jesus Savage,
and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2012.
Details
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[pdf]
(323.7kB
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(2.7MB
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- Austin Villa 2010 Standard Platform Team Report.
Samuel Barrett,
Katie Genter, Matthew Hausknecht,
Todd Hester, Piyush Khandelwal,
Juhyun Lee, Michael
Quinlan, Aibo Tian, Peter Stone,
and Mohan Sridharan.
Technical Report UT-AI-TR-11-01, The University of Texas
at Austin, Department of Computer Sciences, AI Laboratory, 2011.
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(1.3MB
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- Three Humanoid Soccer Platforms: Comparison and Synthesis.
Shivaram
Kalyanakrishnan, Todd Hester, Michael
Quinlan, Yinon Bentor, and Peter
Stone.
In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot
Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
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(379.0kB
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(5.3MB
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- The Essence of Soccer, Can Robots Play Too?.
Peter Stone, Michael
Quinlan, and Todd Hester.
In Ted Richards, editors, Soccer and Philosophy:
Beautiful Thoughts on theBeautiful Game, Popular Culture and Philosophy, pp. 75–88, Open Court Publishing Company,
2010.
Appears in Soccer and Philosophy (available from amazon.com)
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(514.1kB
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- TT-UT Austin Villa 2009: Naos across Texas.
Todd Hester, Michael
Quinlan, Peter Stone, and Mohan
Sridharan.
Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
2009.
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[pdf]
(787.9kB
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- UT Austin Villa 2008: Standing on Two Legs.
Todd Hester, Michael
Quinlan, and Peter Stone.
Technical Report UT-AI-TR-08-8, The University
of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2008.
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(705.9kB
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(6.2MB
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- Intelligent Autonomous Robotics: A Robot Soccer Case Study,
Peter
Stone.
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
Available from Synthesis page.
ISBN: 9781598291262
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(unavailable)
- The UT Austin Villa 2006 RoboCup Four-Legged Team.
Peter Stone, Peggy Fidelman, Nate Kohl, Gregory
Kuhlmann, Tekin Mericli, Mohan Sridharan,
and Shao-en Yu.
Technical Report UT-AI-TR-06-337, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2006.
At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2006.html#06-337
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- The UT Austin Villa 2005 RoboCup Four-Legged Team.
Peter Stone, Kurt Dresner, Peggy
Fidelman, Nate Kohl, Gregory Kuhlmann,
Mohan Sridharan, and Daniel
Stronger.
Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2005.
At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2005.html#05-325
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- The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age.
Peter
Stone, Kurt Dresner, Peggy
Fidelman, Nicholas K. Jong, Nate
Kohl, Gregory Kuhlmann, Mohan
Sridharan, and Daniel Stronger.
Technical Report
UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2004.html#04-313
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(555.3kB
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(1.6MB
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- The UT Austin Villa 2003 Four-Legged Team.
Peter Stone, Kurt
Dresner, Selim T. Erdo\ugan, Peggy Fidelman, Nicholas
K. Jong, Nate Kohl, Gregory Kuhlmann,
Ellie Lin, Mohan Sridharan, Daniel Stronger, and Gurushyam Hariharan.
In Daniel
Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, RoboCup-2003: Robot Soccer World Cup VII,
Springer Verlag, Berlin, 2004.
Extended
version (technical report with full details: "UT Austin Villa 2003: A New RoboCup Four-Legged Team").
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(201.5kB
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- The CMUnited-97 Robotic Soccer Team: Perception and Multi-agent Control.
Manuela
Veloso, Peter Stone, and Kwun Han.
Robotics and Autonomous Systems,
29(2-3):133–143, November 2000.
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(245.3kB
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(497.0kB
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- Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer.
Manuela
Veloso, Peter Stone, and Michael
Bowling.
In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, pp. 134–143,
SPIE, Bellingham, WA, September 1999.
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(108.2kB
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- The CMUnited-98 Champion Small Robot Team.
Manuela Veloso, Michael
Bowling, Sorin Achim, Kwun Han, and Peter Stone.
In Minoru
Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer
World Cup II, Lecture Notes in Artificial Intelligence, pp. 77–92, Springer Verlag, Berlin, 1999.
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(211.2kB
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- The RoboCup Physical Agent Challenge: Phase-I.
Minoru
Asada, Yasuo Kuniyoshi, Alexis Drogoul,
Hajime Asama, Maja
Mataric, Dominique Duhaut, Peter Stone, and Hiroaki
Kitano.
Applied Artificial Intelligence, 12:251–263, 1998.
HTML
version.
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[pdf]
(131.6kB
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[ps]
(97.0kB
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- The CMUnited-97 Small-Robot Team.
Manuela Veloso, Peter
Stone, Kwun Han, and Sorin Achim.
In Hiroaki Kitano, editors,
RoboCup-97: Robot Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 242–256, Springer Verlag,
Berlin, 1998.
HTML version.
Official
version from Publisher's Webpage© Springer-Verlag
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(191.8kB
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- Building a Dedicated Robotic Soccer System.
Sorin Achim, Peter Stone,
and Manuela Veloso.
In Proceedings of the IROS-96 Workshop on RoboCup,
pp. 41–48, Osaka, Japan, November 1996.
HTML
version.
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(159.4kB
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Robotics: RoboCup
- The Human in the Loop: Perspectives and Challenges for RoboCup 2050.
Alessandra Rossi, Maike Paetzel-Prüsmann,
Merel Keijsers, Michael Anderson, Susan Leigh Anderson, Daniel Barry, Jan Gutsche, Justin
Hart, Luca Iocchi, Ainse Kokkelmans, Wouter Kuijpers, Yun Liu, Daniel
Polani, Caleb Roscon, Marcus Scheunemann, Peter Stone, Florian Vahl, René
van de Molengraft, and Oskar von Stryk.
Autonomous
Robots, May 2024.
Official version on publisher's website
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(2.1MB
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- UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
Patrick
MacAlpine, Bo Liu, William Macke,
Caroline Wang, and Peter Stone.
In
Rachid Alami, Joydeep Biswas, Maya
Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International
Publishing, 2022.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021
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(2.5MB
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- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Siddharth Desai, Haresh
Karnan, Josiah P. Hanna, Garrett
Warnell, and Peter Stone.
In IEEE/RSJ International Conference on
Intelligent Robots and Systems(IROS 2020), October 2020.
11-minute video
presentation.
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[pdf]
(1.9MB
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- UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, and Peter Stone.
In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn,
and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pp.
540–52, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2019
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(233.2kB
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(3.8MB
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- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, John Sigmon, and Peter Stone.
In Dirk Holz, Katie
Genter, Maarouf Saad, and Oskar von Stryk, editors,
RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pp. 462–75, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2018
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[pdf]
(486.2kB
)
[ps]
(6.0MB
)
- Overlapping Layered Learning.
Patrick MacAlpine and Peter
Stone.
Artificial Intelligence, 254:21–43, Elsevier, January 2018.
Official version from Publisher's
Webpage
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
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[pdf]
(1.2MB
)
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(3.8MB
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- UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Claude Sammut, Oliver Obst, Flavio Tonidandel,
and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, Lecture Notes in Artificial Intelligence, pp.
473–85, Springer, 2018.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2017
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(973.5kB
)
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(19.4MB
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- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
Ad Hoc Teamwork Robotics Competition.
Katie Genter, Tim
Laue, and Peter Stone.
Autonomous Agents and Multi-Agent Systems
(JAAMAS), 31(4):790–820, Springer, July 2017.
Official version from Publisher's
Webpage
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[pdf]
(1.2MB
)
- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
Patrick
MacAlpine and Peter Stone.
In Gita Sukthankar and Juan
A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
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(518.7kB
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(2.6MB
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[slides.pdf]
(45.5MB
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- UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 515–28, Springer, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2016
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(555.8kB
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(14.4MB
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- Prioritized Role Assignment for Marking.
Patrick MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 306–18, Springer Verlag, Berlin, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/html/marking.html
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(1.7MB
)
[ps]
(13.5MB
)
[slides.pdf]
(157.3MB
)
- UT Austin Villa RoboCup 3D Simulation Base Code Release.
Patrick MacAlpine
and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
Code release at https://github.com/LARG/utaustinvilla3d
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(394.2kB
)
[ps]
(2.1MB
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[slides.pdf]
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- Fast and Precise Black and White Ball Detection for RoboCup Soccer.
Jacob
Menashe, Josh Kelle, Katie Genter, Josiah
Hanna, Elad Liebman, Sanmit
Narvekar, Ruohan Zhang, and Peter
Stone.
In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
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(254.2kB
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[ps]
(716.1kB
)
[slides.pdf]
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- Deep Reinforcement Learning in Parameterized Action Space.
Matthew Hausknecht
and Peter Stone.
In Proceedings of the International Conference on Learning
Representations (ICLR), May 2016.
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(468.3kB
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- UT Austin Villa: Project-Driven Research in AI and Robotics.
Genter, Katie, MacAlpine, Patrick, Menashe, Jacob,
Hannah, Josiah, Liebman, Elad, Narvekar, Sanmit, Zhang,Ruohan, and Stone, Peter.
IEEE Intelligent Systems , 31(02):94–101,
IEEE Computer Society, Los Alamitos, CA, USA, March 2016.
Available from publisher's
webpage
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(unavailable)
- A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer.
David
L. Leottau, Javier Ruiz-del-Solar, Patrick
MacAlpine, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
Details
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(625.8kB
)
- UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine, Josiah Hanna, Jason
Liang, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2015
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(790.2kB
)
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(7.2MB
)
- Adaptation of Surrogate Tasks for Bipedal Walk Optimization.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
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(172.1kB
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(739.5kB
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[slides.pdf]
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- What's Hot at RoboCup (Extended Abstract).
Peter Stone.
In Proceedings
of the Thirtieth AAAI Conference on Artificial Intelligence, February 2016.
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(64.9kB
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- Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League.
Mike Depinet, Patrick MacAlpine,
and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian
Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial
Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/learningFromObservation.html
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(905.3kB
)
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(42.3MB
)
- UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Mike Depinet, Jason
Liang, and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot
Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos
at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2014
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(235.7kB
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(1.9MB
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- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
Patrick
MacAlpine, Mike Depinet, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
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(714.7kB
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(2.5MB
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[slides.pdf]
(105.3MB
)
- SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning.
Patrick
MacAlpine, Eric Price, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/scram.html
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(260.3kB
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(676.5kB
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[slides.pdf]
(40.3MB
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- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
Patrick
MacAlpine, Katie Genter, Samuel
Barrett, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS), September 2014.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
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(491.0kB
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(4.0MB
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[slides.pdf]
(30.4MB
)
- RoboCup Soccer Leagues.
Daniele Nardi, Itsuki
Noda, Fernando Ribeiro, Peter Stone, Oskar
von Stryk, and Manuela Veloso.
AI Magazine, 35(3):77–85, 2014.
Details
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- The 2012 UT Austin Villa Code Release.
Samuel Barrett, Katie
Genter, Yuchen He, Todd
Hester, Piyush Khandelwal, Jacob
Menashe, and Peter Stone.
In RoboCup-2013: Robot Soccer World Cup
XVII, Springer Verlag, 2013.
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(376.3kB
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(2.1MB
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- UT Austin Villa 2012: Standard Platform League World Champions.
Samuel
Barrett, Katie Genter, Yuchen
He, Todd Hester, Piyush Khandelwal,
Jacob Menashe, and Peter Stone.
In
Xiaoping Chen, Peter
Stone, Luis Enrique Sucar, and Tijn
Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2013.
Details
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[pdf]
(740.4kB
)
[ps]
(15.0MB
)
- RoboCup-2012: Robot Soccer World Cup XVI,
Xiaoping
Chen, Peter Stone, Luis Enrique
Sucar, and Tijn van der Zant, editors.
Lecture Notes in Artificial Intelligence,
Springer Verlag, Berlin, 2013.
A book based on RoboCup-2012
Available from the publisher's webpage
ISBN: 978-3-642-39249-8
Details
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(unavailable)
- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
Alon
Farchy, Samuel Barrett, Patrick
MacAlpine, and Peter Stone.
In Proc. of 12th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2013.
The videos referenced in the paper: original
and optimized.
Details
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[pdf]
(486.2kB
)
[ps]
(36.5MB
)
- UT Austin Villa: RoboCup 2012 3D Simulation League Champion.
Patrick
MacAlpine, Nick Collins, Adrian
Lopez-Mobilia, and Peter Stone.
In Xiaoping
Chen, Peter Stone, Luis Enrique
Sucar, and Tijn Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup
XVI, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/results_3d/#highlights
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(654.8kB
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- Positioning to Win: A Dynamic Role Assignment and FormationPositioning System.
Patrick
MacAlpine, Francisco Barrera, and Peter
Stone.
In Xiaoping Chen, Peter
Stone, Luis Enrique Sucar, and Tijn
Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2013.
Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/positioning.html
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[slides.pdf]
(44.0MB
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- Simultaneous Learning and Reshaping of an Approximated Optimization Task.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
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[pdf]
(435.1kB
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(2.1MB
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[slides.pdf]
(35.2MB
)
- UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy.
Jacob
Menashe, Katie Genter, Samuel
Barrett, and Peter Stone.
In The Eighth Workshop on Humanoid Soccer
Robots at Humanoids 2013, October 2013.
Details
BibTeX
Download:
[pdf]
(350.2kB
)
[ps]
(24.1MB
)
[slides.pdf]
(3.1MB
)
- Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions.
Aijun
Bai, Xiaoping Chen, Patrick
MacAlpine, Daniel Urieli, Samuel
Barrett, and Peter Stone.
In Thomas Roefer, Norbert Michael Mayer, Jesus
Savage, and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence,
Springer Verlag, Berlin, 2012.
Details
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[pdf]
(257.0kB
)
[ps]
(829.5kB
)
- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
Samuel
Barrett, Katie Genter, Todd Hester,
Piyush Khandelwal, Michael
Quinlan, Peter Stone, and Mohan
Sridharan.
Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
Laboratory, 2012.
Details
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Download:
[pdf]
(1.1MB
)
[ps]
(32.8MB
)
- A Low Cost Ground Truth Detection System Using the Kinect.
Piyush Khandelwal
and Peter Stone.
In Thomas Roefer, Norbert Michael Mayer, Jesus Savage,
and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2012.
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- Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition.
Patrick MacAlpine, Samuel Barrett,
Daniel Urieli, Victor
Vu, and Peter Stone.
In Proceedings of the Twenty-Sixth AAAI Conference
on Artificial Intelligence (AAAI), July 2012.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html
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- UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition.
Patrick
MacAlpine, Daniel Urieli, Samuel
Barrett, Shivaram Kalyanakrishnan, Francisco
Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua,
Victor Vu, and Peter
Stone.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
Accompanying
videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/components.html
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(646.3kB
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(2.7MB
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- Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk.
Patrick
MacAlpine and Peter Stone.
In AAMAS Adaptive Learning Agents (ALA)
Workshop, June 2012.
Video available at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/holonomicwalk.html
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(525.6kB
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- Video: RoboCup Robot Soccer History 1997 -- 2011.
Manuela Veloso and Peter Stone.
October 2012. Available from https://www.youtube.com/watch?v=WLOv2AFAZhc
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(53.0kB
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- Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker.
Matthew
Hausknecht and Peter Stone.
In Javier
Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
Video and source code available at
http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
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(324.4kB
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- UT Austin Villa 2011 3D Simulation Team Report.
Patrick MacAlpine,
Daniel Urieli, Samuel Barrett,
Shivaram Kalyanakrishnan, Francisco
Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua,
Victor Vu, and Peter
Stone.
Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
2011.
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(1.2MB
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(5.3MB
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- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
Daniel
Urieli, Patrick MacAlpine, Shivaram
Kalyanakrishnan, Yinon Bentor, and Peter
Stone.
In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
May 2011.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
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- Controlled Kicking under Uncertainty.
Samuel Barrett, Katie
Genter, Todd Hester, Michael
Quinlan, and Peter Stone.
In The Fifth Workshop on Humanoid Soccer
Robots at Humanoids 2010, December 2010.
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- Vision Calibration and Processing on a Humanoid Soccer Robot.
Piyush
Khandelwal, Matthew Hausknecht, Juhyun
Lee, Aibo Tian, and Peter Stone.
In
The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
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(402.6kB
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- Color Learning and Illumination Invariance on Mobile Robots: A Survey.
Mohan
Sridharan and Peter Stone.
Robotics and Autonomous Systems (RAS)
Journal, 57(60-7):629–44, June 2009.
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- Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting.
Juhyun
Lee, W. Bradley Knox, and Peter
Stone.
Journal of Physical Agents, 2(2):41–50, July 2008. Special Issue on Human Interaction with Domestic
Robots
Available from journal's web page.
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(2.4MB
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(3.4MB
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- Using RoboCup in university-level computer science education.
Elizabeth
Sklar, Simon Parsons, and Peter
Stone.
Journal on Educational Resources in Computing, 4(2), June 2004. Special issue on robotics in undergraduate
education. Part 1
Available from the publisher's
webpage
JERIC
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- RoboCup as an Introduction to CS Research.
Peter Stone.
In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors,
RoboCup-2003: Robot Soccer World Cup VII, Lecture Notes in Artificial Intelligence, pp. 284–95, Springer Verlag,
Berlin, 2004.
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- Multiagent Competitions and Research: Lessons from RoboCup and TAC.
Peter
Stone.
In Gal A. Kaminka, Pedro U. Lima, and Raul Rojas, editors,
RoboCup-2002: Robot Soccer World Cup VI, Lecture Notes in Artificial Intelligence, pp. 224–237, Springer Verlag,
Berlin, 2003.
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(216.7kB
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(168.6kB
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- RoboCup-2001: The Fifth Robotic Soccer World Championships.
Manuela Veloso,
Tucker Balch, Peter Stone,
Hiroaki Kitano, Fuminori Yamasaki, Ken Endo, Minoru
Asada, M. Jamzad, B. S. Sadjad, V. S. Mirrokni, M. Kazemi, H. Chitsaz, A. Heydarnoori,
M. T. Hajiaghai, and E. Chiniforooshan.
AI Magazine, 23(1):55–68, 2002.
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- RoboCup-2000: Robot Soccer World Cup IV,
Peter Stone, Tucker
Balch, and Gerhard Kraetzschmar, editors.
Lecture Notes
in Artificial Intelligence, Springer Verlag, Berlin, 2001.
A book based on
RoboCup-2000
Available from the publisher's
webpage
ISBN: 3540421858
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- RoboCup-2000: The Fourth Robotic Soccer World Championships.
Peter Stone,
(ed.), Minoru Asada, Tucker
Balch, Raffaelo D'Andrea, Masahiro Fujita, Bernhard Hengst, Gerhard
Kraetzschmar, Pedro Lima, Nuno Lau, Henrik Lund, Daniel Polani, Paul Scerri, Satoshi Tadokoro, Thilo Weigel, and Gordon Wyeth.
AI Magazine,
22(1), 2001.
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- Overview of RoboCup-99.
Silvia Coradeschi, Lars
Karlsson, Peter Stone, Tucker
Balch, Gerhard Kraetzschmar, and Minoru
Asada.
AI Magazine, 21(3), 2000.
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- Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer,
Peter
Stone.
MIT Press, 2000.
A book based on my Ph.D.
thesis
Contents, availability, and on-line appendices
ISBN: 0262194384
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Robotics: Simulated Robot Soccer
- Walking and falling: Using robot simulations to model the role of errors in infant walking.
Ossmy, Ori, Han, Danyang,
MacAlpine, Patrick, Hoch, Justine, Stone, Peter, and Adolph, Karen E..
Developmental Science, 27:e13449, September
2023.
Available from the publisher's webpage
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- UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
Patrick
MacAlpine, Bo Liu, William Macke,
Caroline Wang, and Peter Stone.
In
Rachid Alami, Joydeep Biswas, Maya
Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International
Publishing, 2022.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021
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- UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, and Peter Stone.
In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn,
and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pp.
540–52, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2019
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(3.8MB
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- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.
Patrick
MacAlpine, Faraz Torabi, Brahma
Pavse, John Sigmon, and Peter Stone.
In Dirk Holz, Katie
Genter, Maarouf Saad, and Oskar von Stryk, editors,
RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pp. 462–75, Springer, 2019.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2018
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(486.2kB
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(6.0MB
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- Overlapping Layered Learning.
Patrick MacAlpine and Peter
Stone.
Artificial Intelligence, 254:21–43, Elsevier, January 2018.
Official version from Publisher's
Webpage
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
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(1.2MB
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- UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Claude Sammut, Oliver Obst, Flavio Tonidandel,
and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, Lecture Notes in Artificial Intelligence, pp.
473–85, Springer, 2018.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2017
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(973.5kB
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(19.4MB
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- Variety Wins: Soccer-Playing Robots and Infant Walking.
Ori Ossmy, Justine E. Hoch, Patrick
MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
Frontiers
in Neurorobotics, 12:19, 2018.
Available from the publisher's
webpage
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- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
Patrick
MacAlpine and Peter Stone.
In Gita Sukthankar and Juan
A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
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(518.7kB
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(2.6MB
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[slides.pdf]
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- UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 515–28, Springer, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2016
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- Prioritized Role Assignment for Marking.
Patrick MacAlpine and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 306–18, Springer Verlag, Berlin, 2017.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/html/marking.html
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)
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(13.5MB
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[slides.pdf]
(157.3MB
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- UT Austin Villa RoboCup 3D Simulation Base Code Release.
Patrick MacAlpine
and Peter Stone.
In Sven Behnke, Daniel
D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
Code release at https://github.com/LARG/utaustinvilla3d
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(2.1MB
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- Making Friends on the Fly: Cooperating with New Teammates.
Samuel Barrett,
Avi Rosenfeld, Sarit Kraus,
and Peter Stone.
Artificial Intelligence, October 2016.
Official version from journal website.
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- Deep Reinforcement Learning in Parameterized Action Space.
Matthew Hausknecht
and Peter Stone.
In Proceedings of the International Conference on Learning
Representations (ICLR), May 2016.
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- A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer.
David
L. Leottau, Javier Ruiz-del-Solar, Patrick
MacAlpine, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
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- UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
Patrick
MacAlpine, Josiah Hanna, Jason
Liang, and Peter Stone.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2016.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2015
Details
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(790.2kB
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(7.2MB
)
- Adaptation of Surrogate Tasks for Bipedal Walk Optimization.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
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- Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League.
Mike Depinet, Patrick MacAlpine,
and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian
Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial
Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/learningFromObservation.html
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(905.3kB
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(42.3MB
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- UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.
Patrick
MacAlpine, Mike Depinet, Jason
Liang, and Peter Stone.
In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot
Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2015.
Accompanying videos
at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2014
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- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
Patrick
MacAlpine, Mike Depinet, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
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[slides.pdf]
(105.3MB
)
- SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning.
Patrick
MacAlpine, Eric Price, and Peter
Stone.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/scram.html
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[slides.pdf]
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- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
Patrick
MacAlpine, Katie Genter, Samuel
Barrett, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS), September 2014.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
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(4.0MB
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[slides.pdf]
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)
- The 2012 UT Austin Villa Code Release.
Samuel Barrett, Katie
Genter, Yuchen He, Todd
Hester, Piyush Khandelwal, Jacob
Menashe, and Peter Stone.
In RoboCup-2013: Robot Soccer World Cup
XVII, Springer Verlag, 2013.
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- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
Alon
Farchy, Samuel Barrett, Patrick
MacAlpine, and Peter Stone.
In Proc. of 12th Int. Conf. on Autonomous
Agents and Multiagent Systems (AAMAS), May 2013.
The videos referenced in the paper: original
and optimized.
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(486.2kB
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(36.5MB
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- UT Austin Villa: RoboCup 2012 3D Simulation League Champion.
Patrick
MacAlpine, Nick Collins, Adrian
Lopez-Mobilia, and Peter Stone.
In Xiaoping
Chen, Peter Stone, Luis Enrique
Sucar, and Tijn Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup
XVI, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/results_3d/#highlights
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- Positioning to Win: A Dynamic Role Assignment and FormationPositioning System.
Patrick
MacAlpine, Francisco Barrera, and Peter
Stone.
In Xiaoping Chen, Peter
Stone, Luis Enrique Sucar, and Tijn
Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2013.
Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/positioning.html
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[slides.pdf]
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- Simultaneous Learning and Reshaping of an Approximated Optimization Task.
Patrick
MacAlpine, Elad Liebman, and Peter
Stone.
In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
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(435.1kB
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(2.1MB
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[slides.pdf]
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- Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions.
Aijun
Bai, Xiaoping Chen, Patrick
MacAlpine, Daniel Urieli, Samuel
Barrett, and Peter Stone.
In Thomas Roefer, Norbert Michael Mayer, Jesus
Savage, and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence,
Springer Verlag, Berlin, 2012.
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(257.0kB
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- Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition.
Patrick MacAlpine, Samuel Barrett,
Daniel Urieli, Victor
Vu, and Peter Stone.
In Proceedings of the Twenty-Sixth AAAI Conference
on Artificial Intelligence (AAAI), July 2012.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html
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(461.2kB
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(2.0MB
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[slides.pdf]
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)
- UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition.
Patrick
MacAlpine, Daniel Urieli, Samuel
Barrett, Shivaram Kalyanakrishnan, Francisco
Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua,
Victor Vu, and Peter
Stone.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
Accompanying
videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/components.html
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(646.3kB
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(2.7MB
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[slides.pdf]
(135.4MB
)
- Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk.
Patrick
MacAlpine and Peter Stone.
In AAMAS Adaptive Learning Agents (ALA)
Workshop, June 2012.
Video available at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/holonomicwalk.html
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[pdf]
(525.6kB
)
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(2.2MB
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[slides.pdf]
(159.5MB
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- UT Austin Villa 2011 3D Simulation Team Report.
Patrick MacAlpine,
Daniel Urieli, Samuel Barrett,
Shivaram Kalyanakrishnan, Francisco
Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua,
Victor Vu, and Peter
Stone.
Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
2011.
Details
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(1.2MB
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(5.3MB
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- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
Daniel
Urieli, Patrick MacAlpine, Shivaram
Kalyanakrishnan, Yinon Bentor, and Peter
Stone.
In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
May 2011.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
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[slides.pptx]
(3.8MB
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- Three Humanoid Soccer Platforms: Comparison and Synthesis.
Shivaram
Kalyanakrishnan, Todd Hester, Michael
Quinlan, Yinon Bentor, and Peter
Stone.
In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot
Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
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- The UT Austin Villa 3D Simulation Soccer Team 2008.
Shivaram Kalyanakrishnan,
Yinon Bentor, and Peter Stone.
Technical
Report AI09-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2009.
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- Model-based Reinforcement Learning in a Complex Domain.
Shivaram
Kalyanakrishnan, Peter Stone, and Yaxin
Liu.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World
Cup XI, Lecture Notes in Artificial Intelligence, pp. 171–83, Springer Verlag, Berlin, 2008.
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- Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study.
Shivaram
Kalyanakrishnan, Yaxin Liu, and Peter
Stone.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
72–85, Springer Verlag, Berlin, 2007.
BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
Some simulations referenced in the paper.
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- Batch Reinforcement Learning in a Complex Domain.
Shivaram Kalyanakrishnan
and Peter Stone.
In The Sixth International Joint Conference on Autonomous
Agents and Multiagent Systems, pp. 650–657, ACM, New York, NY, USA, May 2007.
BEST PAPER AWARD NOMINEE.
AAMAS-2007
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- The UT Austin Villa 3D Simulation Soccer Team 2007.
Shivaram Kalyanakrishnan
and Peter Stone.
Technical Report AI-07-348, The University of Texas at
Austin, Department of Computer Sciences, AI Laboratory, 2007.
Supplementary resources at the UT
Austin Villa 3D Simulation page.
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- Empirical Studies in Action Selection for Reinforcement Learning.
Shimon
Whiteson, Matthew E. Taylor, and Peter
Stone.
Adaptive Behavior, 15(1):33–50, March 2007.
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- Know Thine Enemy: A Champion RoboCup Coach Agent.
Gregory Kuhlmann,
William B. Knox, and Peter Stone.
In
Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1463–68, July 2006.
AAAI 2006
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- Keepaway Soccer: From Machine Learning Testbed to Benchmark.
Peter Stone,
Gregory Kuhlmann, Matthew E. Taylor,
and Yaxin Liu.
In Itsuki
Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX,
pp. 93–105, Springer Verlag, Berlin, 2006.
Some simulations
of keepaway referenced in the paper and keepaway software.
Official version from Publisher's
Webpage© Springer-Verlag
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- Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning.
Matthew
Taylor, Shimon Whiteson, and Peter
Stone.
In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
BEST PAPER AWARD at GECCO 2006
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- The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach.
Gregory
Kuhlmann, Peter Stone, and Justin Lallinger.
In Daniele
Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
in Artificial Intelligence, pp. 636–644, Springer Verlag, Berlin, 2005.
Official version from Publisher's
Webpage© Springer-Verlag
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- Reinforcement Learning for RoboCup-Soccer Keepaway.
Peter Stone,
Richard S. Sutton, and Gregory
Kuhlmann.
Adaptive Behavior, 13(3):165–188, 2005.
Contains material that was previously published
in an ICML-2001 paper and a
RoboCup 2003 Symposium paper.
Some simulations
of keepaway referenced in the paper and keepaway software.
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- Evolving Keepaway Soccer Players through Task Decomposition.
Shimon
Whiteson, Nate Kohl, Risto Miikkulainen,
and Peter Stone.
Machine Learning, 59(1):5–30, May 2005.
Some videos of the agents before and after
learning referenced in the paper.
The publisher's official
version
An earlier version appeared in the proceedings of The Genetic
and Evolutionary Computation Conference 2003 (GECCO-2003)
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- Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer.
Gregory
Kuhlmann, Peter Stone, Raymond
Mooney, and Jude Shavlik.
In The AAAI-2004 Workshop on Supervisory
Control of Learning and Adaptive Systems, July 2004.
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- The RoboCup Soccer Server and CMUnited Clients: Implemented Infrastructure for MAS Research.
Itsuki
Noda and Peter Stone.
Autonomous Agents and Multi-Agent Systems,
7(1--2):101–120, July--September 2003.
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- Concurrent Layered Learning.
Shimon Whiteson and Peter Stone.
In Second International Joint Conference on Autonomous Agents
and Multiagent Systems, pp. 193–200, ACM Press, New York, NY, July 2003.
AAMAS-2003
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- ATTUnited-2001: Using Heterogeneous Players.
Peter Stone.
In Andreas
Birk, Silvia Coradeschi, and Satoshi Tadokoro, editors, RoboCup-2001: Robot Soccer
World Cup V, Lecture Notes in Artificial Intelligence, pp. 495–98, Springer Verlag, Berlin, 2002.
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- Keeping the Ball from CMUnited-99.
David McAllester and Peter Stone.
In Peter Stone,
Tucker Balch, and Gerhard
Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, Lecture Notes in Artificial Intelligence, pp. 333–338,
Springer Verlag, Berlin, 2001.
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- Layered Disclosure: Revealing Agents' Internals.
Patrick Riley, Peter
Stone, and Manuela Veloso.
In C. Castelfranchi and Y. Lespérance,
editors, Intelligent Agents VII. Agent Theories, Architectures, and Languages --- 7th. International Workshop, ATAL-2000,
Boston, MA, USA, July 7--9, 2000, Proceedings, Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, Berlin,
2001.
Publisher's Webpage© Springer-Verlag
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- ATT-CMUnited-2000: Third Place Finisher in the RoboCup-2000 Simulator League.
Patrick
Riley, Peter Stone, David
McAllester, and Manuela Veloso.
In P.
Stone, T. Balch, and G.
Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2001.
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- An Architecture for Action Selection in Robotic Soccer.
Peter Stone
and David McAllester.
In Proceedings of the Fifth International
Conference on Autonomous Agents, pp. 316–323, ACM Press, New York, NY, 2001.
Agents-2001
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- Defining and Using Ideal Teammate and Opponent Models.
Peter Stone,
Patrick Riley, and Manuela Veloso.
In
Proceedings of the Twelfth Annual Conference on Innovative Applications of Artificial Intelligence, 2000.
AAAI Homepage
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- The CMUnited-99 Champion Simulator Team.
Peter Stone, Patrick
Riley, and Manuela Veloso.
In M. Veloso,
E. Pagello, and H. Kitano, editors, RoboCup-99: Robot
Soccer World Cup III, Lecture Notes in Artificial Intelligence, pp. 35–48, Springer Verlag, Berlin, 2000.
Extended version (unofficial, but with
some more details) (pdf version)
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- Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork.
Peter Stone and Manuela Veloso.
Artificial
Intelligence, 110(2):241–273, June 1999.
HTML
version.
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- Team-Partitioned, Opaque-Transition Reinforcement Learning.
Peter Stone
and Manuela Veloso.
In Minoru
Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer
World Cup II, Lecture Notes in Artificial Intelligence, pp. 261–72, Springer Verlag, Berlin, 1999. Also in Proceedings
of the Third International Conference on Autonomous Agents, 1999
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- The CMUnited-98 Champion Simulator Team.
Peter Stone, Manuela
Veloso, and Patrick Riley.
In M. Asada
and H. Kitano, editors, RoboCup-98: Robot Soccer World
Cup II, Lecture Notes in Artificial Intelligence, pp. 61–76, Springer Verlag, 1999.
(extended version linked
here)
HTML version.
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- Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer.
Manuela
Veloso, Peter Stone, and Michael
Bowling.
In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, pp. 134–143,
SPIE, Bellingham, WA, September 1999.
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- A Layered Approach to Learning Client Behaviors in the RoboCup Soccer Server.
Peter
Stone and Manuela Veloso.
Applied Artificial Intelligence, 12:165–188,
1998.
HTML version.
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- Towards Collaborative and Adversarial Learning: A Case Study in Robotic Soccer.
Peter
Stone and Manuela Veloso.
International Journal of Human-Computer
Studies, 48(1):83–104, January 1998.
HTML
version.
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- Using Decision Tree Confidence Factors for Multiagent Control.
Peter
Stone and Manuela Veloso.
In Hiroaki
Kitano, editors, RoboCup-97: Robot Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 99–111,
Springer Verlag, Berlin, 1998.
HTML
version.
Official version from Publisher's Webpage© Springer-Verlag
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- The CMUnited-97 Simulator Team.
Peter Stone and Manuela
Veloso.
In Hiroaki Kitano, editors, RoboCup-97: Robot
Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 387–397, Springer Verlag, Berlin, 1998.
HTML version.
Official version
from Publisher's Webpage© Springer-Verlag
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- The RoboCup Synthetic Agent Challenge 97.
Hiroaki Kitano,
Milind Tambe, Peter Stone, Manuela Veloso, Silvia Coradeschi, Eiichi Osawa,
Hitoshi Matsubara, Itsuki Noda, and Minoru
Asada.
In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, pp. 24–29,
Morgan Kaufmann, San Francisco, CA, 1997.
IJCAI-97
HTML
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- Predictive Memory for an Inaccessible Environment.
Mike Bowling,
Peter Stone, and Manuela Veloso.
In
Proceedings of the IROS-96 Workshop on RoboCup, pp. 28–34, Osaka, Japan, November 1996.
HTML
version.
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- Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function.
Peter
Stone and Manuela Veloso.
In Advances in Neural Information Processing
Systems 8, pp. 896–902, MIT Press, Cambridge, MA, 1996.
NIPS-95
HTML version.
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Robotics: Vision
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
Haresh
Karnan, Elvin Yang, Daniel Farkash, Garrett
Warnell, Joydeep Biswas, and Peter
Stone.
In The Conference on Robot Learning (CoRL), November 2023.
Poster,
Video, Project Website
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- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
Sai Kiran Narayanaswami,
Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
Narvekar, and Peter Stone.
In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
2023.
The book
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- Visually Adaptive Geometric Navigation.
Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
Xiao, Garrett Warnell, Joydeep
Biswas, and Peter Stone.
In IEEE International Symposium on Safety,Security,and
Rescue Robotics, November 2023.
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- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
Yifeng
Zhu, Zhenyu Jiang, Peter Stone, and Yuke
Zhu.
In Conference on Robot Learning (CoRL), November 2023.
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(7.3MB
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[poster.pdf]
(5.2MB
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- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
Haresh Karnan, Anirudh Nair, Xuesu Xiao,
Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
Hart, Joydeep Biswas, and Peter Stone.
Robotics
and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
Dataset;
Poster; Video Presentation
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- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
Haresh
Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
Warnell, Peter Stone, and Joydeep Biswas.
In
International Conference on Intelligent Robots and Systems, 2022, October 2022.
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- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
Haresh
Karnan, Garrett Warnell, Xuesu
Xiao, and Peter Stone.
In International Conference on Robotics and
Automation, 2022, May 2022.
Poster,
Video
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- Adversarial Imitation Learning from Video using a State Observer.
Haresh
Karnan, Garrett Warnell, Faraz
Torabi, and Peter Stone.
In International Conference on Robotics
and Automation, 2022, May 2022.
Video
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- Learning a Policy for Opportunistic Active Learning.
Aishwarya Padmakumar, Peter
Stone, and Raymond J. Mooney.
In Proceedings of the Conference on
Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
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- Robot-centric Activity Recognition 'in the Wild'.
Ilaria Gori, Jivko
Sinapov, Priyanka Khante, Peter Stone, and J.K. Aggarwal.
In Proceedings
of the International Conference on Social Robotics (ICSR), October 2015.
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- A Low Cost Ground Truth Detection System Using the Kinect.
Piyush Khandelwal
and Peter Stone.
In Thomas Roefer, Norbert Michael Mayer, Jesus Savage,
and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence, Springer
Verlag, Berlin, 2012.
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- Vision Calibration and Processing on a Humanoid Soccer Robot.
Piyush
Khandelwal, Matthew Hausknecht, Juhyun
Lee, Aibo Tian, and Peter Stone.
In
The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
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- Color Learning and Illumination Invariance on Mobile Robots: A Survey.
Mohan
Sridharan and Peter Stone.
Robotics and Autonomous Systems (RAS)
Journal, 57(60-7):629–44, June 2009.
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- Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting.
Juhyun
Lee, W. Bradley Knox, and Peter
Stone.
Journal of Physical Agents, 2(2):41–50, July 2008. Special Issue on Human Interaction with Domestic
Robots
Available from journal's web page.
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- Structure Based Color Learning on a Mobile Robot under Changing Illumination.
Mohan
Sridharan and Peter Stone.
Autonomous Robots, 23(3):161–182,
2007.
Official versionfrom
the Autonomous Robots publisher's webpage.
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- Planning Actions to Enable Color Learning on a Mobile Robot.
Mohan Sridharan
and Peter Stone.
International Journal of Information and Systems Sciences,
3(3):510–25, 2007.
official
published version
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(unavailable)
- Action Selection for Illumination Invariant Color Learning.
Mohan Sridharan
and Peter Stone.
In The IEEE International Conference on Intelligent
Robots and Systems (IROS), 2007.
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- Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination.
Mohan
Sridharan and Peter Stone.
In The 20th International Joint Conference
on Artificial Intelligence, pp. 2212–2217, January 2007.
IJCAI-07
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- Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data.
Mohan
Sridharan and Peter Stone.
In The Ninth International Conference
on Control, Automation, Robotics and Vision, December 2006.
ICARCV
2006
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- Towards Illumination Invariance in the Legged League.
Mohan Sridharan
and Peter Stone.
In Daniele
Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
in Artificial Intelligence, pp. 196–208, Springer Verlag, Berlin, 2005.
Some videos
of robots referenced in the paper.
Official version from Publisher's
Webpage© Springer-Verlag
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(245.1kB
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(2.1MB
)
- Autonomous Color Learning on a Mobile Robot.
Mohan Sridharan and Peter Stone.
In Proceedings of the Twentieth National Conference on Artificial
Intelligence, July 2005.
Some videos of
the robot referenced in the paper.
AAAI 2005
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- Real-Time Vision on a Mobile Robot Platform.
Mohan Sridharan and Peter Stone.
In IEEE/RSJ International Conference on Intelligent Robots
and Systems (IROS), August 2005.
Some videos
of the robot referenced in the paper.
IROS-2005
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)
Robotics: Service Robots
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
Shivin Dass, Jiaheng
Hu, Ben Abbatematteo, Peter Stone, and Roberto MartÃn-MartÃn.
In Conference
on Robot Learning (CoRL), November 2024.
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- Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
Jiaheng
Hu, Zizhao Wang, Roberto MartÃn-MartÃn, and Peter
Stone.
In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
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- Dobby: A Conversational Service Robot Driven by GPT-4.
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
Hart.
In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
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[poster.pdf]
(892.0kB
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- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
Elliott
Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
Wang, Justin Hart, Reuth Mirsky,
Joydeep Biswas, Junfeng Jiao, and Peter
Stone.
In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
1–15, July 2023.
Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
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- Causal Policy Gradient for Whole-Body Mobile Manipulation.
Jiaheng Hu,
Peter Stone, and Roberto Martin-Martin.
In Robotics: Science and Systems
(RSS), July 2023.
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- Exploring the Cost of Interruptions in Human-Robot Teaming.
Swathi Mannem, William
Macke, Peter Stone, and Reuth
Mirsky.
In IEEE-RAS Humanoids, December 2023.
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(921.5kB
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[poster.pdf]
(294.3kB
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- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
Xiaohan Zhang, Yifeng
Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
Peter Stone, and Shiqi Zhang.
In
International Conference on Intelligent Robots and Systems (IROS), October 2023.
Project
website (includes poster and 5-minute video presentation)
Details
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[pdf]
(4.0MB
)
[slides.pdf]
(6.6MB
)
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
Yifeng
Zhu, Zhenyu Jiang, Peter Stone, and Yuke
Zhu.
In Conference on Robot Learning (CoRL), November 2023.
Details
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(7.3MB
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(5.2MB
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- Visually Grounded Task and Motion Planning for Mobile Manipulation.
Xiaohan Zhang, Yifeng
Zhu, Yan Ding, Yuke Zhu, Peter
Stone, and Shiqi Zhang.
In International Conference on Robotics
and Automation (ICRA), May 2022.
Project page
Code
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- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
Reuth
Mirsky and Peter Stone.
In ICSR workshop on Adaptive Social Interaction
and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
Details
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- Learning and Reasoning for Robot Dialog and Navigation Tasks.
Keting Lu, Shiqi
Zhang, Peter Stone, and Xiaoping
Chen.
In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
Official version from ACL
Digital Library, including a link to the conference presentation
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- Deep R-Learning for Continual Area Sweeping.
Rishi Shah, Yuqian Jiang, Justin
Hart, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
1-minute
video demonstration; 13-minute Video
presentation.
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(1.1MB
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- Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
Jesse
Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
Walker, Yuqian Jiang, Harel
Yedidsion, Justin Hart, Peter Stone,
and Raymond J. Mooney.
The Journal of Artificial Intelligence Research
(JAIR), 67, February 2020.
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- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
Yuqian
Jiang, Fangkai Yang, Shiqi
Zhang, and Peter Stone.
In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
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- Open-World Reasoning for Service Robots.
Yuqian Jiang, Nick
Walker, Justin Hart, and Peter Stone.
In
Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
Accompanying video
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- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
Rishi Shah, Yuqian
Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
Rachel Schlossman, Marika Murphy, Justin Hart, Luis
Sentis, and Peter Stone.
In AAAI Fall Symposium on Artificial Intelligence
and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
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- Desiderata for Planning Systems in General-Purpose Service Robots.
Nick Walker,
Yuqian Jiang, Maya Cakmak, and
Peter Stone.
In Proceedings of the ICAPS Workshop on Planning and Robotics
(PlanRob 2019), July 2019.
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- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
Harel
Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
Stone, and Raymond Mooney.
In International Conference on Social
Robotics (ICSR), pp. 133–143, November 2019.
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- Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
Saeid Amiri, Suhua Wei, Shiqi
Zhang, Jivko Sinapov, Jesse Thomason,
and Peter Stone.
In Proceedings of the 27th International Joint Conference
on Artificial Intelligence (IJCAI-18), July 2018.
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- PRISM: Pose Registration for Integrated Semantic Mapping.
Justin W. Hart,
Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
Stone.
In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
October 2018.
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- Learning a Policy for Opportunistic Active Learning.
Aishwarya Padmakumar, Peter
Stone, and Raymond J. Mooney.
In Proceedings of the Conference on
Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
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- Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions.
Jesse
Thomason, Jivko Sinapov, Raymond
J. Mooney, and Peter Stone.
In Proceedings of the 32nd Conference
on Artificial Intelligence (AAAI), February 2018.
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- CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression.
Santiago Gonzalez,
Vijay Chidambaram, Jivko Sinapov, and Peter
Stone.
In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17),
July 2017.
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- BWIBots: A platform for bridging the gap between AI and human--robot interaction research.
Piyush
Khandelwal, Shiqi Zhang, Jivko
Sinapov, Matteo Leonetti, Jesse Thomason,
Fangkai Yang, Ilaria Gori, Maxwell Svetlik, Priyanka Khante, Vladimir
Lifschitz, J. K. Aggarwal, Raymond Mooney, and Peter
Stone.
The International Journal of Robotics Research, 36(5--7):635–59, 2017.
Accompanying videos
at https://youtu.be/2UJG4-ejVww
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- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
Piyush
Khandelwal and Peter Stone.
In International Conference on Autonomous
Agents and Multiagent Systems (AAMAS), May 2017.
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- Iterative Human-Aware Mobile Robot Navigation.
Shih-Yun Lo, Benito Fernandez, and Peter
Stone.
In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics:
Science and System (RSS), July 2017.
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- Leveraging Commonsense Reasoning and Multimodal Perception for Robot Spoken Dialog Systems.
Dongcai Lu, Shiqi
Zhang, Peter Stone, and Xiaoping
Chen.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
2017.
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- Opportunistic Active Learning for Grounding Natural Language Descriptions.
Jesse
Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin
Hart, Peter Stone, and Raymond
J. Mooney.
In Proceedings of the 1st Annual Conference on Robot Learning (CoRL-17), pp. 67–76, PMLR, Mountain
View, California, November 2017.
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- Integrated Commonsense Reasoning and Probabilistic Planning.
Shiqi Zhang
and Peter Stone.
In Proceedings of 2017 ICAPS Workshop on Planning and
Robotics, June 2017.
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- State Aggregation through Reasoning in Answer Set Programming.
Ginevra Gaudioso, Matteo
Leonetti, and Peter Stone.
In Proceedings of the IJCAI Workshop on
Autonomous Mobile Service Robots (WSR 16), July 2016.
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- Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors.
Jivko
Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone.
In Proceedings
of the 25th International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
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- Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy.
Jesse Thomason,
Jivko Sinapov, Maxwell Svetlik, Peter
Stone, and Raymond Mooney.
In Proceedings of the 25th international
joint conference on Artificial Intelligence (IJCAI), July 2016.
Demo Video
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- Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots.
Shiqi
Zhang, Dongcai Lu, Xiaoping Chen, and Peter
Stone.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
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- Robot-centric Activity Recognition 'in the Wild'.
Ilaria Gori, Jivko
Sinapov, Priyanka Khante, Peter Stone, and J.K. Aggarwal.
In Proceedings
of the International Conference on Social Robotics (ICSR), October 2015.
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- Leading the Way: An Efficient Multi-robot Guidance System.
Piyush Khandelwal,
Samuel Barrett, and Peter Stone.
In
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
Accompanying videos at
https://www.youtube.com/watch?v=os1BjHgM5ao&feature=youtu.be
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- Learning to Interpret Natural Language Commands through Human-Robot Dialog.
Jesse
Thomason, Shiqi Zhang, Raymond
Mooney, and Peter Stone.
In Proceedings of the 2015 International
Joint Conference on Artificial Intelligence (IJCAI), July 2015.
Demo
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- CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot.
Shiqi
Zhang and Peter Stone.
In Proceedings of the 29th Conference on Artificial
Intelligence (AAAI), January 2015.
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- Planning in Action Language $\cal BC$ while Learning Action Costs for Mobile Robots.
Piyush
Khandelwal, Fangkai Yang, Matteo
Leonetti, Vladimir Lifschitz, and Peter
Stone.
In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
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- Multi-robot Human Guidance using Topological Graphs.
Piyush Khandelwal
and Peter Stone.
In AAAI Spring 2014 Symposium on Qualitative Representations
for Robots (AAAI-SSS), March 2014.
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- Planning in Answer Set Programming while Learning Action Costs for Mobile Robots.
Fangkai
Yang, Piyush Khandelwal, Matteo
Leonetti, and Peter Stone.
In AAAI Spring 2014 Symposium on Knowledge
Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
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Robotics: Human-Robot Interaction
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
Amir Hossain Raj, Zichao
Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter
Stone, Joydeep Biswas, and and Xuesu
Xiao.
In International Conference on Robotics and Automation, May 2024.
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- Dobby: A Conversational Service Robot Driven by GPT-4.
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
Hart.
In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
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- Kinematic coordinations capture learning during human-exoskeleton interaction.
Keya
Ghonasgi, Reuth Mirsky, Nisha Bhargava, Adrian M Haith, Peter
Stone, and Ashish D Deshpande.
Scientific Reports, 13:10322, June 2023.
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- A Novel Control Law for Multi-joint Human-Robot Interaction Tasks While Maintaining Postural Coordination.
Keya
Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter
Stone, and Ashish D Deshpande.
In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
October 2023.
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- Exploring the Cost of Interruptions in Human-Robot Teaming.
Swathi Mannem, William
Macke, Peter Stone, and Reuth
Mirsky.
In IEEE-RAS Humanoids, December 2023.
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- Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System.
Keya
Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter
Stone, and Ashish D Deshpande.
In Proceedings of the 35th International Conference on Intelligent Robots and Systems
(IROS), October 2022.
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- Incorporating Gaze into Social Navigation.
Justin Hart, Reuth
Mirsky, Xuesu Xiao, and Peter
Stone.
In RSS Workshop on Social Robot Navigation, July 2021.
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- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
Blake Holman, Abrar
Anwar, Akash Singh, Mauricio Tec, Justin
Hart, and Peter Stone.
In Proceedings of the International Conference
on Robotics and Automation (ICRA), May 2021.
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- Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle.
Yu-Sian Jiang, Garrett
Warnell, and Peter Stone.
In Proceedings of the 35th AAAI Conference
on Artificial Intelligence (AAAI), Feb 2021.
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- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
Reuth
Mirsky and Peter Stone.
In ICSR workshop on Adaptive Social Interaction
and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
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- The EMPATHIC Framework for Task Learning from Implicit Human Feedback.
Yuchen
Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott
Niekum, and W. Bradley Knox.
In Proceedings of the 4th Conference on Robot
Learning (CoRL 2020), November 2020.
5-minute video presentation;
47-minute in-depth talk.
Project website.
Raw
data from experiments.
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- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
Justin Hart,
Reuth Mirsky, Xuesu Xiao,
Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
Stone.
In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
Video presentation
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- Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
Jesse
Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
Walker, Yuqian Jiang, Harel
Yedidsion, Justin Hart, Peter Stone,
and Raymond J. Mooney.
The Journal of Artificial Intelligence Research
(JAIR), 67, February 2020.
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- Agents teaching agents: a survey on inter-agent transfer learning.
Felipe Leno
Da Silva, Garrett Warnell, Anna
Helena Reali Costa, and Peter Stone.
Autonomous Agents and Multi-Agent
Systems, Dec 2019.
Official version from JAAMAS
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- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
Jesse
Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
Walker, Yuqian Jiang, Harel
Yedidsion, Justin Hart, Peter Stone,
and Raymond Mooney.
In Proceedings of the International Conference on
Robotics and Automation (ICRA 2019), May 2019.
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- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
Harel
Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
Stone, and Raymond Mooney.
In International Conference on Social
Robotics (ICSR), pp. 133–143, November 2019.
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- Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability.
Rolando Fernandez, Nathan
John, Sean Kirmani, Justin Hart, Jivko
Sinapov, and Peter Stone.
In Proceedings of the 27th IEEE International
Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.
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Trading Agents
- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
Daniel
Urieli and Peter Stone.
In Proceedings of the 15th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
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- Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
Daniel
Urieli and Peter Stone.
In Proceedings of the 30th Conference on
Artificial Intelligence (AAAI 2016), February 2016.
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- TacTex'13: A Champion Adaptive Power Trading Agent.
Daniel Urieli
and Peter Stone.
In Proceedings of the Twenty-Eighth Conference on Artificial
Intelligence (AAAI 2014), July 2014.
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- Designing Adaptive Trading Agents.
David Pardoe and Peter
Stone.
ACM SIGecom Exchanges, 10(2):37–9, June 2011.
SIGecom
Exchanges
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- The 2007 TAC SCM Prediction Challenge.
David Pardoe and Peter
Stone.
In Wolfgang Ketter, Han La Poutré, Norman Sadeh, Onn
Shehory, and William Walsh, editors, Agent-Mediated Electronic Commerce and Trading Agent Design and Alaysis, Lecture
Notes in Business Information Processing (LNBIP), pp. 175–89, Springer Verlag, 2010.
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- Designing Safe, Profitable Automated Stock Trading Agents Using Evolutionary Algorithms.
Harish Subramanian, Subramanian Ramamoorthy, Peter
Stone, and Benjamin Kuipers.
In Proceedings of the Genetic and
Evolutionary Computation Conference, July 2006.
GECCO 2006
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- Three Automated Stock-Trading Agents: A Comparative Study.
Alexander
Sherstov and Peter Stone.
In P. Faratin and J.A. Rodriguez-Aguilar,
editors, Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems (AMEC
2004), Lecture Notes in Artificial Intelligence, pp. 173–187, Springer Verlag, Berlin, 2005.
Official version
from Publisher's Webpage© Springer-Verlag
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- Two Stock-Trading Agents: Market Making and Technical Analysis.
Yi Feng, Ronggang Yu, and Peter
Stone.
In Peyman Faratin, David C. Parkes, Juan A. Rodriguez-Aguilar,
and William E. Walsh, editors, Agent Mediated Electronic Commerce V: Designing Mechanisms and Systems, Lecture
Notes in Artificial Intelligence, pp. 18–36, Springer Verlag, 2004.
AMEC-2003
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- Guest Editors' Introduction: Agents and Markets.
Amy Greenwald,
Nicholas R. Jennings, and Peter
Stone.
IEEE Intelligent Systems, 18(6):12–14, November/December 2003.
IEEEIntelligent
Systems special issue on agents and markets.
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- Performance Analysis of a Counter-intuitive Automated Stock-Trading Strategy.
Ronggang Yu and Peter
Stone.
In Proceedings of the Fifth International Conference on Electronic Commerce, Pittsburgh, PA, October
2003.
ICEC-2003
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Trading Agents: Auctions
- A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations.
David
Pardoe and Peter Stone.
In Proceedings of the 10th International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
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- Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge.
David
Pardoe, Peter Stone, Maytal
Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak.
Informs Journal
on Computing, 22(3):353–370, 2010.
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- TacTex09: A Champion Bidding Agent for Ad Auctions.
David Pardoe,
Doran Chakraborty, and Peter
Stone.
In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010),
May 2010.
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- Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition,
Michael
P. Wellman, Amy Greenwald, and Peter
Stone.
MIT Press, 2007.
Available from
MIT Press page.
ISBN: 0-262-23260-X
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- The First International Trading Agent Competition: Autonomous Bidding Agents.
Peter
Stone and Amy Greenwald.
Electronic Commerce Research,
5(2):229–65, April 2005.
Official version from publisher's
website © Springer-Verlag
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- Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions.
Peter
Stone, Robert E. Schapire, Michael
L. Littman, János A. Csirik, and David
McAllester.
Journal of Artificial Intelligence Research, 19:209–242, 2003.
Available from journal's
web page.
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- Multiagent Competitions and Research: Lessons from RoboCup and TAC.
Peter
Stone.
In Gal A. Kaminka, Pedro U. Lima, and Raul Rojas, editors,
RoboCup-2002: Robot Soccer World Cup VI, Lecture Notes in Artificial Intelligence, pp. 224–237, Springer Verlag,
Berlin, 2003.
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- The 2001 Trading Agent Competition.
Michael P. Wellman, Amy Greenwald, Peter Stone,
and Peter R. Wurman.
Electronic Markets, 13(1):4–12, May 2003.
Available from the publisher's
webpage
An earlier version appeared in the Fourteenth Conference on Innovative Applications of Artificial Intelligence,
pages 935-941, Edmonton, July 2002.
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- Self-enforcing Strategic Demand Reduction.
Paul S. A. Reitsma,
Peter Stone, János A. Csirik, and
Michael L. Littman.
In Agent Mediated Electronic Commerce IV: Designing
Mechanisms and Systems, Lecture Notes in Artificial Intelligence, pp. 289–306, Springer Verlag, 2002.
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- Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation.
Robert
E. Schapire, Peter Stone, David
McAllester, Michael L. Littman, and János
A. Csirik.
In Proceedings of the Nineteenth International Conference on Machine Learning, 2002.
ICML-2002
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- FAucS: An FCC Spectrum Auction Simulator for Autonomous Bidding Agents.
János
A. Csirik, Michael L. Littman, Satinder
Singh, and Peter Stone.
In Electronic Commerce: Proceedings of the
Second International Workshop, pp. 139–151, Springer Verlag, Heidelberg, Germany, 2001.
WELCOM-01
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- Autonomous Bidding Agents in the Trading Agent Competition.
Amy
Greenwald and Peter Stone.
IEEE Internet Computing, 5(2):52–60,
March/April 2001.
Magazine's website
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- ATTac-2000: An Adaptive Autonomous Bidding Agent.
Peter Stone, Michael L. Littman, Satinder Singh,
and Michael Kearns.
Journal of Artificial Intelligence Research,
15:189–206, June 2001.
Available from journal's web page.
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Trading Agents: Mechanism Design
- Program Embeddings for Rapid Mechanism Evaluation.
Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
and Peter Stone.
In ICRA Workshop on Multi-Robot Learning, May 2023.
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- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
Michael
Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
Operations
Research, March 2021.
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- Adaptive Mechanism Design: A Metalearning Approach.
David Pardoe,
Peter Stone, Maytal
Saar-Tsechansky, and Kerem Tomak.
In The Eighth International Conference
on Electronic Commerce, pp. 92–102, August 2006.
ICEC 2006. Contains material
from Adaptive Auctions: Learning to Adjust to Bidders,
Workshop on Information Technologies and Systems (WITS), 2005.
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- Developing Adaptive Auction Mechanisms.
David Pardoe and Peter
Stone.
ACM SIGecom Exchanges, 5(3):1–10, April 2005.
SIGecom
Exchanges
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Trading Agents: Supply Chain Management
- An Autonomous Agent for Supply Chain Management.
David Pardoe and
Peter Stone.
In Gedas Adomavicius and Alok Gupta, editors, Handbooks
in Information Systems Series: Business Computing, pp. 141–72, Emerald Group, 2009.
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- Adapting Price Predictions in TAC SCM.
David Pardoe and Peter
Stone.
In John Collins, Peyman Faratin, Simon
Parsons, Juan A. Rodriguez-Aguilar, Norman
M. Sadeh, Onn Shehory, and Elizabeth
Sklar, editors, Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis, Lecture Notes in Business
Information Processing, pp. 30–45, Springer Verlag, 2009.
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webpage
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- TacTex-2005: A Champion Supply Chain Management Agent.
David Pardoe
and Peter Stone.
In Proceedings of the Twenty-First National Conference
on Artificial Intelligence, pp. 1489–94, July 2006.
AAAI
2006
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- Predictive Planning for Supply Chain Management.
David Pardoe and
Peter Stone.
In Proceedings of the International Conference on Automated
Planning and Scheduling, June 2006.
ICAPS 2006
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- Bidding for Customer Orders in TAC SCM.
David Pardoe and Peter
Stone.
In P. Faratin and J.A. Rodriguez-Aguilar,
editors, Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems (AMEC
2004), Lecture Notes in Artificial Intelligence, pp. 143–157, Springer Verlag, Berlin, 2005.
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- TacTex-03: A Supply Chain Management Agent.
David Pardoe and Peter Stone.
ACM SIGecom Exchanges: Special Issue on Trading Agent
Design and Analysis, 4(3):19–28, Winter 2004.
SIGecom
Exchanges
Extended
version citable as University of Texas at Austin AI lab technical
report number UT-AI-TR-04-308.
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- Now, Later, and Lasting: 10 Priorities for AI Research, Policy, and Practice.
Eric Horvitz, Vincent Conitzer, Sheila
McIlraith, and Peter Stone.
Communications of the ACM, 67(6):39–40,
May 2024.
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online version
arXiv version
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- Will Robots Triumph over World Cup Winners by 2050?.
Peter Stone.
IEEE
Spectrum, 60(7):40–9, July 2023.
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version
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- Challenges and Opportunities of Applying Reinforcement Learning to Autonomous Racing.
Peter
R. Wurman, Peter Stone, and Michael Sprannger.
IEEE Intelligent
Systems, 37(3):20–3, May-June 2022.
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online version
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- Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The BARN Challenge at ICRA 2022.
Xuesu Xiao, Zifan Xu, Zizhao
Wang, Yunlong Song, Garrett Warnell, Peter
Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep
Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, and Philip Dames.
IEEE Robotics
\& Automation Magazine, 29(4):148–56, Dec. 2022.
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online version.
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- RoboCup 2021 Worldwide: A Successful Robotics Competition During a Pandemic.
Peter
Stone, Luca Iocchi, Flavio Tonidandel, and Changjiu Zhou.
IEEE Robotics \& Automation Magazine, 28(4):114–19,
December 2021.
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- A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society.
Barbara
J. Grosz and Peter Stone.
Communications of the ACM, 61(12),
December 2018.
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online version
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- Artificial Intelligence and Life in 2030.
Peter Stone, Rodney Brooks,
Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram
Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes,
William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, and Astro
Teller.
One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University,
Stanford, CA, 2016.
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- Who Speaks for AI.
Eric Eaton, Tom Dietterich, Maria Gini, Barbara J. Grosz, Charles
L. Isbell, Subbarao Kambhamp, Michael Littman, Francesca Rossi, Stuart
Russell, Peter Stone, Toby Walsh, and Michael Wooldridge.
AI Matters,
2(2), December 2015.
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