Peter Stone's Selected Publications

• Classified by Topic • Classified by Publication Type • Sorted by Date • Sorted by First Author Last Name • Classified by Funding Source •

Sorted by First Author Last Name

• Achim • Agarwal • Agmon • Ahmadi • Albert • Albrecht • Alkobi • Amiri • Asada • Au • Bai • Bajaj • Baker • Banerjee • Barrett • Beeson • Booth • Bowling • Capobianco • Carlino • Chakraborty • Chen • Chuck • Coradeschi • Csirik • Cui • Dass • Depinet • Desai • Djeu • Dresner • Du • Durugkar • Eaton • Fajardo • Fang • Farchy • Fasel • Feng • Fernandez • Fidelman • Fok • Gaudioso • Genter • Ghonasgi • Gonzalez • Gori • Grasemann • Greenwald • Grizou • Grosz • Guo • Hanina • Hanna • Haresh • Hart • Hauser • Hausknecht • Hester • Holman • Horvitz • Hu • Hudson • Huerta • Isbell • Iwata • Jiang • Jong • Jung • Kalyanakrishnan • Karnan • Katie • Khandelwal • Kim • Kitano • Knox • Kockelman • Kohl • Kompella • Koppel • Kuhlmann • Kumar • Lee • Leon • Leonetti • Leottau • Levine • Li • Liebman • Lin • Littman • Liu • Lo • Lu • MacAlpine • MacGlashan • Macke • Mannem • Masetty • McAllester • Menashe • Mirsky • Mocanu • Morrill • Nagarajan • Nair • Narayanaswami • Nardi • Narvekar • Noda • Nweye • Ori • Ossmy • Padmakumar • Pardoe • Park • Pavse • Perille • Quinlan • Rabideau • Rahman • Raj • Rambha • Ravi • Reisinger • Reitsma • Riley • Rossi • Saggar • Scerri • Schapire • Setapen • Shah • Sharon • Sherstov • Shperberg • Silva • Sinapov • Singh • Sklar • Sokar • Soltoggio • Sridharan • Stark • Stone • Stronger • Subramanian • Sung • Suriadinata • Svetlik • Taylor • Thomason • Torabi • Tumer • Tuyls • Urieli • VanMiddlesworth • Vasco • Veloso • Walker • Wang • Warnell • Weaver • Wellman • White • Whiteson • Wildstrom • Wu • Wurman • Xiao • Xu • Yang • Yedidsion • Yu • Yue • Zhang • Zhu •

Achim

• 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.
  Details     BibTeX     Download: [pdf] (159.4kB )  [ps] (336.0kB )  

Agarwal

• 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     BibTeX     Download: [pdf] (3.4MB )  [slides.pptx] (13.6MB )  [poster.pdf] (1.8MB )  

Agmon

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (229.4kB )  [ps] (757.7kB )  

• 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.
  Details     BibTeX     Download: [pdf] (412.4kB )  [ps] (5.4MB )  

• 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
  Details     BibTeX     Download: [pdf] (323.8kB )  [ps] (1.9MB )  

Ahmadi

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (261.6kB )  [ps] (1.0MB )  

• 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).
  Details     BibTeX     Download: [pdf] (105.0kB )  [ps] (128.8kB )  

• 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
  Details     BibTeX     Download: [pdf] (171.3kB )  [ps] (314.6kB )  

• 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     Download: [pdf] (186.7kB )  [ps] (243.1kB )  

Albert

• Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
  Michael Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
  Operations Research, March 2021.
  Details     BibTeX     Download: [pdf] (692.5kB )  

• 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.
  Details     BibTeX     Download: [pdf] (348.6kB )  [slides.pdf] (2.8MB )  

• 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.
  Details     BibTeX     Download: [pdf] (366.4kB )  [slides.pdf] (2.7MB )  

Albrecht

• 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
  Details     BibTeX     Download: [pdf] (670.7kB )  

• 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
  Details     BibTeX     Download: [pdf] (304.3kB )  

• 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
  Details     BibTeX     Download: [pdf] (608.2kB )  [slides.pdf] (1.2MB )  

Alkobi

• 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     BibTeX     Download: [pdf] (350.4kB )  

Amiri

• 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.
  Details     BibTeX     Download: [pdf] (2.5MB )  

Asada

• 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.
  Details     BibTeX     Download: [pdf] (131.6kB )  [ps] (97.0kB )  

Au

• 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     BibTeX     Download: [pdf] (2.6MB )  

• 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     BibTeX     Download: [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     BibTeX     Download: [pdf] (684.9kB )  [ps] (2.7MB )  

• 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     BibTeX     Download: [pdf] (1.1MB )  [ps] (31.7MB )  

• 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     BibTeX     Download: [pdf] (417.4kB )  [ps] (2.0MB )  

Bai

• 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     BibTeX     Download: [pdf] (257.0kB )  [ps] (829.5kB )  

Bajaj

• 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 )  

Baker

• 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
  Details     BibTeX     Download: (unavailable)

Banerjee

• 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     BibTeX     Download: [pdf] (118.1kB )  [ps] (198.5kB )  

• 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     BibTeX     Download: [pdf] (172.9kB )  [ps] (464.0kB )  

Barrett

• 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 )  

• 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     BibTeX     Download: [pdf] (740.4kB )  [ps] (15.0MB )  

• 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 )  

• 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     BibTeX     Download: [pdf] (190.1kB )  [ps] (2.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (177.6kB )  [ps] (1.1MB )  [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     BibTeX     Download: [pdf] (361.8kB )  [ps] (11.4MB )  [slides.pdf] (616.4kB )  

• 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.
  Details     BibTeX     Download: [pdf] (136.1kB )  [ps] (384.8kB )  

• 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     BibTeX     Download: [pdf] (357.3kB )  [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
  Details     BibTeX     Download: [pdf] (688.8kB )  [ps] (5.7MB )  

• 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     BibTeX     Download: [pdf] (1.1MB )  [ps] (32.8MB )  

• 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     BibTeX     Download: [pdf] (1.3MB )  [ps] (38.0MB )  

Beeson

• 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
  Details     BibTeX     Download: [pdf] (2.1MB )  [ps] (6.6MB )  

Booth

• 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     BibTeX     Download: [pdf] (1.4MB )  

Bowling

• 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.
  Details     BibTeX     Download: [pdf] (135.0kB )  [ps] (141.4kB )  

Capobianco

• 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 )  

Carlino

• 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     BibTeX     Download: [pdf] (318.1kB )  [ps] (1.4MB )  

• 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     BibTeX     Download: [pdf] (727.1kB )  [ps] (14.3MB )  

Chakraborty

• Multiagent Learning in the Presence of Memory-Bounded Agents.
  Doran Chakraborty and Peter Stone.
  Autonomous Agents and Multiagent Systems (JAAMAS), Springer, 2013.
  Details     BibTeX     Download: [pdf] (676.7kB )  [ps] (447.9kB )  

• 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     BibTeX     Download: [pdf] (202.3kB )  [ps] (408.2kB )  

• 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.
  Details     BibTeX     Download: [pdf] (223.3kB )  [ps] (521.1kB )  

• 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.
  Details     BibTeX     Download: [pdf] (196.9kB )  [ps] (474.1kB )  

• 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
  Details     BibTeX     Download: [pdf] (232.4kB )  [ps] (669.2kB )  

• 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.
  Details     BibTeX     Download: [pdf] (629.0kB )  [ps] (1.6MB )  

Chen

• 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     BibTeX     Download: (unavailable)

• 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 )  

Chuck

• 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 )  

Coradeschi

• Overview of RoboCup-99.
  Silvia Coradeschi, Lars Karlsson, Peter Stone, Tucker Balch, Gerhard Kraetzschmar, and Minoru Asada.
  AI Magazine, 21(3), 2000.
  Details     BibTeX     Download: [ps] (2.2MB )  

Csirik

• 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
  Details     BibTeX     Download: [pdf] (202.3kB )  [ps] (170.8kB )  

Cui

• 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     Download: [pdf] (769.8kB )  [slides.pdf] (2.1MB )  [poster.pdf] (1.8MB )  

• 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 )  

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (6.4MB )  [slides.pptx] (59.4MB )  

Dass

• Learning to Look: Seeking Information for Decision Making via Policy Factorization.
  Shivin Dass, Jiaheng Hu, Ben Abbatematteo, Peter Stone, and Roberto Martín-Martín.
  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 )  

Depinet

• 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
  Details     BibTeX     Download: [pdf] (905.3kB )  [ps] (42.3MB )  

Desai

• 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     BibTeX     Download: [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     Download: [pdf] (1.9MB )  

Djeu

• 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 )  

Dresner

• 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     BibTeX     Download: [pdf] (1.3MB )  [ps] (2.2MB )  

• 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
  Details     BibTeX     Download: [pdf] (81.4kB )  [ps] (168.2kB )  

• 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     BibTeX     Download: [pdf] (189.9kB )  [ps] (287.7kB )  

• 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     BibTeX     Download: [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     BibTeX     Download: [pdf] (233.8kB )  [ps] (492.0kB )  

• 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     BibTeX     Download: [pdf] (836.3kB )  [ps] (1.3MB )  

• 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     BibTeX     Download: [pdf] (79.9kB )  [ps] (197.6kB )  

• 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     Download: [pdf] (227.5kB )  [ps] (376.8kB )  

Du

• 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.
  Details     BibTeX     Download: [pdf] (2.2MB )  

Durugkar

• 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
  Details     BibTeX     Download: [pdf] (5.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (3.9MB )  

• TD Learning with Constrained Gradients.
  Ishan Durugkar and Peter Stone.
  In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
  Details     BibTeX     Download: [pdf] (381.4kB )  

Eaton

• 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.
  Details     BibTeX     Download: (unavailable)

Fajardo

• 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     BibTeX     Download: [pdf] (591.8kB )  

Fang

• 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
  Details     BibTeX     Download: [pdf] (456.7kB )  [ps] (983.9kB )  [slides.pptx] (6.2MB )  

Farchy

• 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     BibTeX     Download: [pdf] (486.2kB )  [ps] (36.5MB )  

Fasel

• 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
  Details     BibTeX     Download: [pdf] (407.2kB )  [ps] (1.9MB )  

Feng

• 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
  Details     BibTeX     Download: [pdf] (512.0kB )  [ps] (912.4kB )  

Fernandez

• 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.
  Details     BibTeX     Download: [pdf] (8.5MB )  [slides.pdf] (983.4kB )  

Fidelman

• 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     BibTeX     Download: [pdf] (186.9kB )  [ps] (1.6MB )  

Fok

• 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 )  

Gaudioso

• 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     Download: [pdf] (776.6kB )  

Genter

• 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 )  

• Ad Hoc Teamwork Behaviors for Influencing a Flock.
  Katie Genter and Peter Stone.
  Acta Polytechnica, 56(1), 2016.
  Details     BibTeX     Download: [pdf] (421.5kB )  [ps] (1.6MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.5MB )  [ps] (1.6MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.2MB )  [ps] (4.5MB )  [slides.pdf] (433.7kB )  

• 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     BibTeX     Download: [pdf] (426.7kB )  [ps] (1.4MB )  [slides.pdf] (1.6MB )  

• 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.
  Details     BibTeX     Download: [pdf] (358.4kB )  [ps] (1.4MB )  [slides.pdf] (15.3MB )  

• 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.
  Details     BibTeX     Download: [pdf] (246.7kB )  [ps] (563.3kB )  [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     BibTeX     Download: [pdf] (179.8kB )  [ps] (413.8kB )  [slides.pdf] (13.0MB )  

Ghonasgi

• 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.
  Details     BibTeX     Download: [pdf] (1.9MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.2MB )  

• 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.
  Details     BibTeX     Download: [pdf] (5.4MB )  

• 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     Download: [pdf] (1.6MB )  

Gonzalez

• 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.
  Details     BibTeX     Download: [pdf] (241.6kB )  

Gori

• 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.
  Details     BibTeX     Download: [pdf] (361.3kB )  

Grasemann

• 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.
  Details     BibTeX     Download: [pdf] (280.9kB )  [ps] (1.6MB )  

Greenwald

• 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.
  Details     BibTeX     Download: [pdf] (545.6kB )  

• 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
  Details     BibTeX     Download: [pdf] (817.8kB )  [ps] (1.4MB )  

Grizou

• 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.
  Details     BibTeX     Download: [pdf] (339.0kB )  

Grosz

• 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.
  Official online version
  Details     BibTeX     Download: [pdf] (84.2kB )  

Guo

• 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.
  Details     BibTeX     Download: [pdf] (1.6MB )  

Hanina

• 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     BibTeX     Download: [pdf] (404.2kB )  

Hanna

• 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.
  Details     BibTeX     Download: [pdf] (3.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (3.7MB )  

• 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.
  Details     BibTeX     Download: [pdf] (2.7MB )  [slides.pdf] (4.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (3.1MB )  

• 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     BibTeX     Download: [pdf] (2.2MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.2MB )  [slides.pdf] (1.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (663.8kB )  [ps] (572.6kB )  [slides.pdf] (1.3MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.3MB )  [slides.pdf] (1.3MB )  

• Towards a Data Efficient Off-Policy Policy Gradient.
  Josiah Hanna and Peter Stone.
  In AAAI Spring Symposium on Data Efficient Reinforcement Learning, March 2018.
  Details     BibTeX     Download: [pdf] (345.4kB )  

• 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     BibTeX     Download: [pdf] (117.5kB )  [ps] (355.2kB )  [slides.pdf] (4.7MB )  

Haresh

• 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 )  

Hart

• 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
  Details     BibTeX     Download: [pdf] (3.2MB )  

• 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.
  Details     BibTeX     Download: [pdf] (4.4MB )  

• Incorporating Gaze into Social Navigation.
  Justin Hart, Reuth Mirsky, Xuesu Xiao, and Peter Stone.
  In RSS Workshop on Social Robot Navigation, July 2021.
  Details     BibTeX     Download: [pdf] (4.8MB )  [slides.pdf] (3.5MB )  

Hauser

• "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
  Details     BibTeX     Download: (unavailable)

Hausknecht

• 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.
  Details     BibTeX     Download: [pdf] (1.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.3MB )  [ps] (3.1MB )  

• 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
  Details     BibTeX     Download: [pdf] (324.4kB )  [ps] (2.8MB )  

• Deep Reinforcement Learning in Parameterized Action Space.
  Matthew Hausknecht and Peter Stone.
  In Proceedings of the International Conference on Learning Representations (ICLR), May 2016.
  Details     BibTeX     Download: [pdf] (468.3kB )  

• 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.
  Details     BibTeX     Download: [pdf] (880.9kB )  [ps] (3.3MB )  

• 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     BibTeX     Download: [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     BibTeX     Download: [pdf] (252.7kB )  [ps] (1.9MB )  

• Grounded Semantic Networks for Learning Shared Communication Protocols.
  Matthew Hausknecht and Peter Stone.
  In Deep Reinforcement Learning, NIPS Workshop, December 2016.
  Details     BibTeX     Download: [pdf] (899.9kB )  

• 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.
  Details     BibTeX     Download: [pdf] (2.5MB )  

• 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.
  Details     BibTeX     Download: [pdf] (253.9kB )  

• Deep Imitation Learning for Parameterized Action Spaces.
  Matthew Hausknecht, Yilun Chen, and Peter Stone.
  In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (483.4kB )  

• 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.
  Details     BibTeX     Download: [pdf] (65.1kB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (3.8MB )  

Hester

• Intrinsically motivated model learning for developing curious robots.
  Todd Hester and Peter Stone.
  Artificial Intelligence, 247:170–86, June 2017.
  from journal website.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (474.7kB )  [ps] (1.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (234.7kB )  [ps] (2.9MB )  

• 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.
  Details     BibTeX     Download: [pdf] (258.7kB )  [ps] (2.4MB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (253.9kB )  [ps] (554.1kB )  

• 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     BibTeX     Download: [pdf] (1.5MB )  [ps] (25.3MB )  

• 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
  Details     BibTeX     Download: [pdf] (181.5kB )  [ps] (425.5kB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (127.0kB )  [ps] (363.0kB )  

• 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     BibTeX     Download: [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     BibTeX     Download: [pdf] (705.9kB )  [ps] (6.2MB )  

Holman

• 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.
  Details     BibTeX     Download: [pdf] (5.7MB )  

Horvitz

• 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.
  Official online version
  arXiv version
  Details     BibTeX     Download: [pdf] (151.4kB )  

Hu

• Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
  Jiaheng Hu, Zizhao Wang, Roberto Martín-Martín, and Peter Stone.
  In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
  Details     BibTeX     Download: [pdf] (2.7MB )  

• Causal Policy Gradient for Whole-Body Mobile Manipulation.
  Jiaheng Hu, Peter Stone, and Roberto Martin-Martin.
  In Robotics: Science and Systems (RSS), July 2023.
  Details     BibTeX     Download: [pdf] (4.0MB )  

Hudson

• 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 )  

• 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     BibTeX     Download: [pdf] (393.0kB )  

Huerta

• 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
  Details     BibTeX     Download: [pdf] (1.4MB )  [slides.pdf] (2.3MB )  

Isbell

• 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     BibTeX     Download: (unavailable)

Iwata

• 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.
  Details     BibTeX     Download: [pdf] (807.5kB )  

Jiang

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (911.3kB )  [poster.pdf] (1.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.8MB )  [slides.pdf] (1.8MB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (813.5kB )  

• 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     BibTeX     Download: [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     Download: [pdf] (5.8MB )  [slides.pptx] (32.7MB )  

Jong

• 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.
  Details     BibTeX     Download: [pdf] (173.0kB )  [ps] (431.7kB )  

• 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
  Details     BibTeX     Download: [pdf] (157.5kB )  [ps] (370.2kB )  

• 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
  Details     BibTeX     Download: [pdf] (136.4kB )  [ps] (325.7kB )  

• 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.
  Details     BibTeX     Download: [pdf] (321.1kB )  [ps] (1.0MB )  

• 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     BibTeX     Download: [pdf] (102.1kB )  [ps] (249.8kB )  [slides.pdf] (323.4kB )  

• Model-Based Exploration in Continuous State Spaces.
  Nicholas K. Jong and Peter Stone.
  In The Seventh Symposium on Abstraction, Reformulation, and Approximation, July 2007.
  Details     BibTeX     Download: [pdf] (324.3kB )  [ps] (1.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (42.4kB )  

• 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
  Details     BibTeX     Download: (unavailable)

Jung

• 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.
  Details     BibTeX     Download: [pdf] (1.8MB )  [ps] (1.8MB )  

• 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.
  Details     BibTeX     Download: [pdf] (417.0kB )  [ps] (6.5MB )  [slides.pdf] (505.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (746.9kB )  [ps] (2.3MB )  [slides.pdf] (957.5kB )  

• 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 )  

Kalyanakrishnan

• 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
  Details     BibTeX     Download: [pdf] (858.5kB )  [ps] (2.4MB )  

• 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.
  Details     BibTeX     Download: [pdf] (200.5kB )  [ps] (1.4MB )  

• 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     BibTeX     Download: [pdf] (379.0kB )  [ps] (5.3MB )  

• 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.
  Details     BibTeX     Download: [pdf] (200.9kB )  [ps] (515.0kB )  

• 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.
  Details     BibTeX     Download: [pdf] (992.2kB )  [ps] (1.6MB )  

• 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.
  Details     BibTeX     Download: [pdf] (230.2kB )  [ps] (519.5kB )  

• 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.
  Details     BibTeX     Download: [pdf] (257.1kB )  [ps] (679.3kB )  

• 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
  Details     BibTeX     Download: [pdf] (366.4kB )  [ps] (1.7MB )  

• 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
  Details     BibTeX     Download: [pdf] (186.4kB )  [ps] (384.8kB )  

• 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.
  Details     BibTeX     Download: [pdf] (163.8kB )  [ps] (196.0kB )  

• 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.
  Details     BibTeX     Download: [pdf] (292.6kB )  [ps] (983.9kB )  

• 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.
  Details     BibTeX     Download: [pdf] (273.4kB )  [ps] (5.7MB )  

Karnan

• 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 )  

• 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     BibTeX     Download: [pdf] (25.7MB )  

• 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     BibTeX     Download: [pdf] (933.2kB )  

• 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 )  

Katie

• 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
  Details     BibTeX     Download: (unavailable)

Khandelwal

• 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
  Details     BibTeX     Download: [pdf] (4.4MB )  

• 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     BibTeX     Download: [pdf] (323.7kB )  [ps] (2.7MB )  

• 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.
  Details     BibTeX     Download: [pdf] (346.4kB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.8MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.3MB )  [slides.pdf] (1.7MB )  

• 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
  Details     BibTeX     Download: [pdf] (694.2kB )  

• 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 )  

• 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     BibTeX     Download: [pdf] (402.6kB )  [ps] (14.8MB )  

Kim

• 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.
  Details     BibTeX     Download: [pdf] (4.0MB )  

Kitano

• 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 version.
  Details     BibTeX     Download: [pdf] (135.1kB )  [ps] (97.9kB )  

Knox

• 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     Download: [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
  Details     BibTeX     Download: [pdf] (696.3kB )  [ps] (5.6MB )  

• 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.
  Details     BibTeX     Download: [pdf] (3.9MB )  

• 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
  Details     BibTeX     Download: [pdf] (2.6MB )  

• 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     BibTeX     Download: (unavailable)

• 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 )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (929.6kB )  [ps] (4.9MB )  

• 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
  Details     BibTeX     Download: [pdf] (447.6kB )  [ps] (3.9MB )  

• 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
  Details     BibTeX     Download: [pdf] (422.9kB )  [ps] (3.5MB )  

• 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
  Details     BibTeX     Download: [pdf] (540.2kB )  [ps] (3.7MB )  

• 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
  Details     BibTeX     Download: [pdf] (1.1MB )  [ps] (12.8MB )  

• 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     BibTeX     Download: [pdf] (372.4kB )  [ps] (41.6MB )  

• 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
  Details     BibTeX     Download: [pdf] (400.8kB )  [ps] (2.1MB )  

Kockelman

• 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     BibTeX     Download: (unavailable)

• 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)

• 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)

Kohl

• 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
  Details     BibTeX     Download: [pdf] (210.0kB )  [ps] (1.4MB )  

• 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     BibTeX     Download: [pdf] (301.5kB )  [ps] (3.2MB )  

Kompella

• Event Tables for Efficient Experience Replay.
  Varun Kompella, Thomas Walsh, Samuel Barrett, Peter Wurman, and Peter Stone.
  Transactions on Machine Learning Research (TMLR), 2023.
  Details     BibTeX     Download: [pdf] (6.8MB )  

Koppel

• 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
  Details     BibTeX     Download: [pdf] (648.8kB )  

Kuhlmann

• 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
  Details     BibTeX     Download: [pdf] (112.7kB )  [ps] (287.8kB )  

• 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     BibTeX     Download: [pdf] (377.0kB )  [ps] (601.6kB )  

• 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
  Details     BibTeX     Download: [pdf] (124.1kB )  [ps] (156.2kB )  

• 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
  Details     BibTeX     Download: [pdf] (126.0kB )  [ps] (286.1kB )  

• 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     BibTeX     Download: [pdf] (170.3kB )  [ps] (498.2kB )  

Kumar

• 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.
  Details     BibTeX     Download: [pdf] (9.7MB )  

Lee

• 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     BibTeX     Download: [pdf] (2.4MB )  [ps] (3.4MB )  

Leon

• 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)
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (1.4MB )  [poster.pdf] (1.5MB )  

Leonetti

• 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     BibTeX     Download: [pdf] (3.2MB )  

Leottau

• 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     BibTeX     Download: [pdf] (625.8kB )  

Levine

• Multistep Inverse Is Not All You Need.
  Alexander Levine, Peter Stone, and Amy Zhang.
  Reinforcement Learning Conference, 2024.
  Details     BibTeX     Download: [pdf] (1.8MB )  [slides.pdf] (4.8MB )  [poster.pdf] (2.7MB )  

Li

• 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.
  Details     BibTeX     Download: [pdf] (765.8kB )  [ps] (2.5MB )  

Liebman

• 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.
  Details     BibTeX     Download: [pdf] (4.0MB )  

• Representative Selection in Nonmetric Datasets.
  Elad Liebman, Benny Chor, and Peter Stone.
  "Applied Artificial Intelligence", 29:807–838, 2015.
  Details     BibTeX     Download: [pdf] (846.3kB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.7MB )  

• 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.
  Details     BibTeX     Download: [pdf] (258.5kB )  

• 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.
  Details     BibTeX     Download: [pdf] (377.0kB )  

• 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.
  Details     BibTeX     Download: [pdf] (591.1kB )  [slides.pdf] (678.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (832.6kB )  [ps] (6.3MB )  [slides.pdf] (2.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.5MB )  [ps] (38.4MB )  [slides.pdf] (2.6MB )  

Lin

• 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     BibTeX     Download: [pdf] (387.5kB )  

Littman

• 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
  Details     BibTeX     Download: [pdf] (244.7kB )  [ps] (272.4kB )  

• 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
  Details     BibTeX     Download: [pdf] (181.2kB )  [ps] (149.4kB )  

Liu

• 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 )  

• FAMO: Fast Adaptive Multitask Optimization.
  Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
  In Neural Information Processing Systems Foundation, July 2023.
  Details     BibTeX     Download: [pdf] (3.0MB )  

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (1.8MB )  

• 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.
  Details     BibTeX     Download: [pdf] (4.2MB )  [slides.pdf] (1.6MB )  [poster.pdf] (885.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (440.4kB )  [slides.pdf] (710.5kB )  

• 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
  Details     BibTeX     Download: [pdf] (9.7MB )  

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (2.2MB )  [poster.pdf] (1.1MB )  

• 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     BibTeX     Download: [pdf] (151.7kB )  [ps] (1.6MB )  

Lo

• 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     BibTeX     Download: [pdf] (4.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (2.0MB )  

Lu

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (1.6MB )  

MacAlpine

• 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
  Details     BibTeX     Download: [pdf] (1.2MB )  [ps] (3.8MB )  

• 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
  Details     BibTeX     Download: [pdf] (2.5MB )  

• 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
  Details     BibTeX     Download: [pdf] (233.2kB )  [ps] (3.8MB )  

• 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
  Details     BibTeX     Download: [pdf] (486.2kB )  [ps] (6.0MB )  

• 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
  Details     BibTeX     Download: [pdf] (973.5kB )  [ps] (19.4MB )  

• 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.
  Details     BibTeX     Download: [pdf] (518.7kB )  [ps] (2.6MB )  [slides.pdf] (45.5MB )  

• 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
  Details     BibTeX     Download: [pdf] (555.8kB )  [ps] (14.4MB )  

• 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
  Details     BibTeX     Download: [pdf] (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
  Details     BibTeX     Download: [pdf] (394.2kB )  [ps] (2.1MB )  [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
  Details     BibTeX     Download: [pdf] (790.2kB )  [ps] (7.2MB )  

• 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
  Details     BibTeX     Download: [pdf] (235.7kB )  [ps] (1.9MB )  

• 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
  Details     BibTeX     Download: [pdf] (654.8kB )  [ps] (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
  Details     BibTeX     Download: [pdf] (255.9kB )  [ps] (722.6kB )  [slides.pdf] (44.0MB )  

• 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
  Details     BibTeX     Download: [pdf] (714.7kB )  [ps] (2.5MB )  [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
  Details     BibTeX     Download: [pdf] (260.3kB )  [ps] (676.5kB )  [slides.pdf] (40.3MB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (461.2kB )  [ps] (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
  Details     BibTeX     Download: [pdf] (646.3kB )  [ps] (2.7MB )  [slides.pdf] (135.4MB )  

• 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     BibTeX     Download: [pdf] (172.1kB )  [ps] (739.5kB )  [slides.pdf] (165.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (435.1kB )  [ps] (2.1MB )  [slides.pdf] (35.2MB )  

• 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
  Details     BibTeX     Download: [pdf] (525.6kB )  [ps] (2.2MB )  [slides.pdf] (159.5MB )  

• 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     BibTeX     Download: [pdf] (1.2MB )  [ps] (5.3MB )  

MacGlashan

• 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
  Details     BibTeX     Download: [pdf] (11.6MB )  

Macke

• 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 )  

Mannem

• 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 )  

Masetty

• 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
  Details     BibTeX     Download: [pdf] (594.9kB )  [slides.pdf] (1.5MB )  

McAllester

• 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.
  Details     BibTeX     Download: [pdf] (107.1kB )  [ps] (66.1kB )  

Menashe

• 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.
  Details     BibTeX     Download: [pdf] (254.2kB )  [ps] (716.1kB )  [slides.pdf] (1.5MB )  

• 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.
  Details     BibTeX     Download: [pdf] (693.2kB )  [ps] (18.4MB )  

• 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.
  Details     BibTeX     Download: [pdf] (538.3kB )  [ps] (5.3MB )  

• 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 )  

Mirsky

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (198.8kB )  

• 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 )  

• 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.
  Details     BibTeX     Download: [pdf] (679.2kB )  

• 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
  Details     BibTeX     Download: [pdf] (1.2MB )  [slides.pdf] (1.4MB )  

• 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
  Details     BibTeX     Download: [pdf] (1011.6kB )  

Mocanu

• 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.
  Details     BibTeX     Download: [pdf] (1.5MB )  

Morrill

• 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
  Details     BibTeX     Download: [pdf] (5.5MB )  

Nagarajan

• 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.
  Details     BibTeX     Download: [pdf] (6.6MB )  

Nair

• 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     BibTeX     Download: [pdf] (895.8kB )  

Narayanaswami

• 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
  Details     BibTeX     Download: [pdf] (572.2kB )  

• 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     BibTeX     Download: [pdf] (1.3MB )  [poster.pdf] (916.2kB )  

Nardi

• 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     BibTeX     Download: (unavailable)

Narvekar

• 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     Download: [pdf] (1.4MB )  

• 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     Download: [pdf] (953.0kB )  [slides.pdf] (5.6MB )  

• 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     BibTeX     Download: [pdf] (826.2kB )  [slides.pdf] (5.8MB )  

• 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     Download: [pdf] (630.0kB )  [slides.pdf] (10.2MB )  

• 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     BibTeX     Download: [pdf] (330.4kB )  [slides.pdf] (3.8MB )  

Noda

• 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.
  Details     BibTeX     Download: [pdf] (271.2kB )  [ps] (459.0kB )  

• 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)

Nweye

• 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.
  Details     BibTeX     Download: [pdf] (5.9MB )  

Ori

• 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
  Details     BibTeX     Download: (unavailable)

Ossmy

• 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
  Details     BibTeX     Download: [pdf] (2.9MB )  

Padmakumar

• 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.
  Details     BibTeX     Download: [pdf] (394.3kB )  

Pardoe

• 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.
  Details     BibTeX     Download: [pdf] (530.9kB )  [ps] (9.2MB )  

• Designing Adaptive Trading Agents.
  David Pardoe and Peter Stone.
  ACM SIGecom Exchanges, 10(2):37–9, June 2011.
  SIGecom Exchanges
  Details     BibTeX     Download: [pdf] (159.7kB )  

• Developing Adaptive Auction Mechanisms.
  David Pardoe and Peter Stone.
  ACM SIGecom Exchanges, 5(3):1–10, April 2005.
  SIGecom Exchanges
  Details     BibTeX     Download: [pdf] (155.6kB )  [ps] (212.4kB )  

• 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.
  Details     BibTeX     Download: [pdf] (145.3kB )  [ps] (161.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.0MB )  [ps] (2.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (392.2kB )  [ps] (736.6kB )  

• 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
  Details     BibTeX     Download: [pdf] (328.7kB )  [ps] (524.0kB )  

• 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.
  Official version from Publisher's Webpage© Springer-Verlag
  Details     BibTeX     Download: [pdf] (174.3kB )  [ps] (283.8kB )  

• 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.
  Details     BibTeX     Download: [pdf] (313.6kB )  [ps] (280.8kB )  

• 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     BibTeX     Download: [pdf] (600.5kB )  [ps] (1.7MB )  

• 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.
  Details     BibTeX     Download: [pdf] (564.3kB )  [ps] (1.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (334.2kB )  [ps] (511.6kB )  

• 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
  Details     BibTeX     Download: [pdf] (200.7kB )  [ps] (196.5kB )  

• 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 )  

Park

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (1.3MB )  

Pavse

• 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     Download: [pdf] (405.1kB )  [slides.pptx] (115.4MB )  

• 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.
  Details     BibTeX     Download: [pdf] (738.4kB )  [slides.pdf] (5.2MB )  

• 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
  Details     BibTeX     Download: [pdf] (327.2kB )  

Perille

• 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 )  

Quinlan

• 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     BibTeX     Download: [pdf] (1.3MB )  [ps] (10.6MB )  

Rabideau

• 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     BibTeX     Download: (unavailable)

Rahman

• 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 )  

Raj

• 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 )  

Rambha

• 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
  Details     BibTeX     Download: [pdf] (1.6MB )  

Ravi

• 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 )  

Reisinger

• 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
  Details     BibTeX     Download: [pdf] (434.0kB )  [ps] (1.7MB )  

Reitsma

• 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.
  Details     BibTeX     Download: [pdf] (141.7kB )  [ps] (125.4kB )  

Riley

• 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
  Details     BibTeX     Download: [pdf] (96.6kB )  [ps] (881.8kB )  

• 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.
  Details     BibTeX     Download: [pdf] (114.6kB )  [ps] (82.2kB )  

Rossi

• 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
  Details     BibTeX     Download: [pdf] (2.1MB )  

Saggar

• 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     BibTeX     Download: [pdf] (1.1MB )  [ps] (26.8MB )  

Scerri

• 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
  Details     BibTeX     Download: [pdf] (765.1kB )  

Schapire

• 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
  Details     BibTeX     Download: [pdf] (159.5kB )  [ps] (137.2kB )  

Setapen

• 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 )  

Shah

• 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.
  Details     BibTeX     Download: [pdf] (374.2kB )  [slides.pdf] (1.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (4.5MB )  

Sharon

• 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     BibTeX     Download: [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     BibTeX     Download: [pdf] (1.1MB )  [ps] (7.1MB )  [slides.pptx] (140.9MB )  

• 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 )  

• 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     BibTeX     Download: [pdf] (1002.7kB )  [ps] (5.2MB )  [slides.pptx] (11.1MB )  

Sherstov

• 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
  Details     BibTeX     Download: [pdf] (167.0kB )  [ps] (248.6kB )  

• 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
  Details     BibTeX     Download: [pdf] (187.7kB )  [ps] (583.4kB )  [slides.pdf] (193.7kB )  

• 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
  Details     BibTeX     Download: [pdf] (205.5kB )  [ps] (774.2kB )  

Shperberg

• Relaxed Exploration Constrained Reinforcement Learning.
  Shahaf S. Shperberg, Bo Liu, and Peter Stone.
  In Conference on Autonomous Agents and Multiagent Systems, May 2024.
  Details     BibTeX     Download: [pdf] (3.4MB )  

• 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     BibTeX     Download: [pdf] (8.9MB )  

Silva

• 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 )  

• 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     BibTeX     Download: [pdf] (1.6MB )  

Sinapov

• 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     BibTeX     Download: [pdf] (6.6MB )  [slides.pdf] (5.2MB )  

• 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     BibTeX     Download: [pdf] (337.2kB )  

Singh

• 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
  Details     BibTeX     Download: [pdf] (316.3kB )  [ps] (319.2kB )  

Sklar

• 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
  Details     BibTeX     Download: (unavailable)

Sokar

• 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
  Details     BibTeX     Download: [pdf] (3.7MB )  [slides.pptx] (16.7MB )  

Soltoggio

• 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.
  Details     BibTeX     Download: [pdf] (2.8MB )  

Sridharan

• 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.
  Details     BibTeX     Download: [pdf] (1.3MB )  [ps] (6.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (2.0MB )  [ps] (8.6MB )  

• 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
  Details     BibTeX     Download: (unavailable)

• 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
  Details     BibTeX     Download: [pdf] (245.1kB )  [ps] (2.1MB )  

• Action Selection for Illumination Invariant Color Learning.
  Mohan Sridharan and Peter Stone.
  In The IEEE International Conference on Intelligent Robots and Systems (IROS), 2007.
  Details     BibTeX     Download: [pdf] (176.5kB )  [ps] (490.5kB )  

• 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
  Details     BibTeX     Download: [pdf] (129.5kB )  [ps] (184.9kB )  

• 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
  Details     BibTeX     Download: [pdf] (444.1kB )  [ps] (2.3MB )  

• 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
  Details     BibTeX     Download: [pdf] (901.5kB )  [ps] (6.4MB )  

• 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
  Details     BibTeX     Download: [pdf] (396.1kB )  [ps] (5.0MB )  

• 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
  Details     BibTeX     Download: [pdf] (217.6kB )  [ps] (2.0MB )  [slides.pdf] (2.5MB )  

Stark

• 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 )  

Stone

• 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
  Details     BibTeX     Download: (unavailable)

• 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.
  Details     BibTeX     Download: (unavailable)

• 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
  Details     BibTeX     Download: (unavailable)

• 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
  Details     BibTeX     Download: (unavailable)

• A Broader, More Inclusive Definition of AI.
  Peter Stone.
  Journal of Artificial General Intelligence, 11(2):63–65, 2020.
  Details     BibTeX     Download: [pdf] (50.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (499.6kB )  [ps] (734.2kB )  

• 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.
  Details     BibTeX     Download: [pdf] (117.9kB )  [ps] (91.0kB )  

• 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     BibTeX     Download: [pdf] (260.5kB )  [ps] (3.6MB )  

• 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     BibTeX     Download: [pdf] (1.2MB )  [ps] (2.0MB )  

• 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
  Details     BibTeX     Download: [pdf] (398.7kB )  [ps] (679.1kB )  

• 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.
  Details     BibTeX     Download: [pdf] [ps] 

• 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.
  Details     BibTeX     Download: [pdf] (326.9kB )  [ps] (305.2kB )  

• 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.
  Details     BibTeX     Download: [pdf] (292.1kB )  [ps] (1.1MB )  

• 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.
  Details     BibTeX     Download: [pdf] (209.2kB )  [ps] (318.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (189.1kB )  [ps] (1.2MB )  

• 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.
  Details     BibTeX     Download: [pdf] (137.7kB )  [ps] (3.2MB )  

• Will Robots Triumph over World Cup Winners by 2050?.
  Peter Stone.
  IEEE Spectrum, 60(7):40–9, July 2023.
  Official online version
  Details     BibTeX     Download: (unavailable)

• 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.
  Official online version
  Details     BibTeX     Download: (unavailable)

• 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.
  Details     BibTeX     Download: [pdf] (661.0kB )  [ps] (20.2MB )  

• 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     BibTeX     Download: [pdf] (121.3kB )  [ps] (514.1kB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (567.7kB )  [ps] (2.3MB )  

• 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.
  Details     BibTeX     Download: [pdf] (150.1kB )  [ps] (1.2MB )  

• 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.
  Details     BibTeX     Download: [pdf] (216.7kB )  [ps] (168.6kB )  

• 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.
  Details     BibTeX     Download: [pdf] (152.3kB )  [ps] (362.7kB )  

• 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
  Details     BibTeX     Download: [pdf] (151.4kB )  [ps] (144.7kB )  

• 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
  Details     BibTeX     Download: [pdf] (157.2kB )  [ps] (128.0kB )  

• 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     BibTeX     Download: [pdf] (154.0kB )  [ps] (170.7kB )  

• What's Hot at RoboCup (Extended Abstract).
  Peter Stone.
  In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 2016.
  Details     BibTeX     Download: [pdf] (64.9kB )  

• 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     BibTeX     Download: [pdf] (180.6kB )  [ps] (285.3kB )  

• 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     Download: [pdf] (308.5kB )  [ps] (379.3kB )  

• 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     BibTeX     Download: [pdf] (177.5kB )  [ps] (174.3kB )  

• 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
  Details     BibTeX     Download: [pdf] (90.3kB )  [ps] (101.4kB )  

• TPOT-RL Applied to Network Routing.
  Peter Stone.
  In Proceedings of the Seventeenth International Conference on Machine Learning, pp. 935–942, 2000.
  ICML-2000
  Details     BibTeX     Download: [pdf] (161.7kB )  [ps] (395.0kB )  

• 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.
  Details     BibTeX     Download: [pdf] (300.1kB )  [ps] (1.8MB )  

• 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     BibTeX     Download: [pdf] (146.6kB )  [ps] (125.5kB )  

• 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 )  

• 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     BibTeX     Download: [pdf] (52.6kB )  [ps] (56.8kB )  

• 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.
  Available online
  Details     BibTeX     Download: (unavailable)

• 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     BibTeX     Download: [pdf] (2.7MB )  

• 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
  Details     BibTeX     Download: [pdf] (123.7kB )  [ps] (127.2kB )  

• 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
  Details     BibTeX     Download: [pdf] (186.2kB )  [ps] (243.4kB )  

• 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
  Details     BibTeX     Download: [pdf] (555.3kB )  [ps] (1.6MB )  

• 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").
  Details     BibTeX     Download: [pdf] (201.5kB )  [ps] (170.3kB )  

• 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.
  Details     BibTeX     Download: [pdf] (112.8kB )  [ps] (79.3kB )  

• 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)
  Details     BibTeX     Download: [pdf] (197.0kB )  [ps] (235.3kB )  

• 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.
  Details     BibTeX     Download: [pdf] (195.1kB )  [ps] (174.7kB )  

• 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
  Details     BibTeX     Download: [pdf] (128.3kB )  [ps] (107.2kB )  

Stronger

• 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 )  

• 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     BibTeX     Download: [pdf] (372.6kB )  [ps] (1.4MB )  

• 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.
  Details     BibTeX     Download: [pdf] (159.7kB )  [ps] (342.4kB )  

• 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     BibTeX     Download: [pdf] (235.3kB )  [ps] (489.4kB )  

• 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 )  

• 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     Download: [pdf] (271.4kB )  [ps] (2.2MB )  

Subramanian

• 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
  Details     BibTeX     Download: [pdf] (214.6kB )  [ps] (813.6kB )  

Sung

• 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 )  

• 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 )  

• 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 )  

Suriadinata

• 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 )  

Svetlik

• 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     BibTeX     Download: [pdf] (2.0MB )  

Taylor

• 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     BibTeX     Download: [pdf] (399.8kB )  [ps] (579.4kB )  

• 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     BibTeX     Download: [pdf] (499.9kB )  [ps] (831.3kB )  

• An Introduction to Inter-task Transfer for Reinforcement Learning.
  Matthew E. Taylor and Peter Stone.
  AI Magazine, 32(1):15–34, 2011.
  Details     BibTeX     Download: [pdf] (237.0kB )  [ps] (773.0kB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (233.3kB )  [ps] (391.7kB )  

• 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     BibTeX     Download: [pdf] (149.0kB )  [ps] (202.5kB )  

• 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
  Details     BibTeX     Download: [pdf] (99.7kB )  [ps] (190.4kB )  

• 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
  Details     BibTeX     Download: [pdf] (220.7kB )  [ps] (325.4kB )  

• 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     BibTeX     Download: [pdf] (222.5kB )  [ps] (525.2kB )  

• 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
  Details     BibTeX     Download: [pdf] (235.9kB )  [ps] (562.2kB )  

• 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     BibTeX     Download: [pdf] (147.3kB )  [ps] (449.9kB )  

• 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
  Details     BibTeX     Download: [pdf] (230.4kB )  [ps] (620.1kB )  

• 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
  Details     BibTeX     Download: [pdf] (144.9kB )  [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     BibTeX     Download: [pdf] (139.9kB )  [ps] (215.4kB )  

Thomason

• 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.
  Details     BibTeX     Download: [pdf] (4.0MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.6MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.2MB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (1.4MB )  [slides.pdf] (1.1MB )  

Torabi

• 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     BibTeX     Download: [pdf] (742.7kB )  

• 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     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• 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     BibTeX     Download: [pdf] (2.3MB )  [slides.pptx] (26.0MB )  

• 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     Download: [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     BibTeX     Download: [pdf] (6.1MB )  

Tumer

• 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.
  Details     BibTeX     Download: (unavailable)

Tuyls

• 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.
  Details     BibTeX     Download: [pdf] (509.0kB )  

Urieli

• 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     Download: [pdf] (11.9MB )  

• 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.
  Details     BibTeX     Download: [pdf] (1.2MB )  

• 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.
  Details     BibTeX     Download: [pdf] (257.8kB )  [ps] (7.3MB )  [slides.pdf] (3.8MB )  

• 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
  Details     BibTeX     Download: [pdf] (2.3MB )  [ps] (1.4MB )  [slides.pdf] (3.6MB )  

• 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 )  

• 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
  Details     BibTeX     Download: [pdf] (530.9kB )  [ps] (1.6MB )  [slides.pptx] (3.8MB )