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RESEARCH STATEMENT

I am a computer scientist with research specialization in artificial intelligence. My long-term research goal is to create complete, robust, autonomous agents that can learn to interact with other intelligent agents in a wide range of complex, dynamic environments. These agents must sense their environment; engage in high-level cognitive decision-making; and then execute their actions in the environment. Moreover, to be effective, they should improve their performance automatically over time and reason explicitly about the behaviors of other agents, including teammates and adversaries. Thus, my research contributions are mainly in the areas of machine learning; autonomous agents and multiagent systems; and robotics. Application domains have included robot soccer, autonomous bidding agents, intelligent traffic management, general-purpose service robots, and autonomous vehicles.



PROFESSIONAL PREPARATION



APPOINTMENTS



AWARDS AND RESEARCH DISTINCTIONS



TEACHING



THESIS COMMITTEES



OTHER ADVISING



PROFESSIONAL ACTIVITIES



INVITED DISTINGUISHED LECTURES



INVITED TALKS



PUBLICATIONS

All listed publications are available and cross-listed by type, date, topic, and co-author at
http://www.cs.utexas.edu/users/pstone/papers.html

Books

1
Xiaoping Chen, Peter Stone, Luis Enrique Sucar, and Tijn van der Zant, editors.
RoboCup-2012: Robot Soccer World Cup XVI, volume 7500 of Lecture Notes in Artificial Intelligence.
Springer Verlag, Berlin, 2013.

2
Kagan Tumer, Pinar Yolum, Liz Sonenberg, and Peter Stone, editors.
Proceedings of the Tenth International Conference on Autonomous Agents and Multiagent Systems.
International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), May 2011.

3
Michael P. Wellman, Amy Greenwald, and Peter Stone.
Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition.
MIT Press, 2007. (monograph)

4
Peter Stone.
Intelligent Autonomous Robotics: A Robot Soccer Case Study.
Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2007. (monograph)

5
Peter Stone and Gerhard Weiss, editors.
Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems.
Association for Computing Machinery (ACM), May 2006.

6
Peter Stone, Tucker Balch, and Gerhard Kraetzschmar, editors.
RoboCup-2000: Robot Soccer World Cup IV.
volume 2019 of Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2001.

7
Peter Stone.
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer.
MIT Press, 2000. (monograph)



Journal Articles

1
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.
The human in the loop: Perspectives and challenges for RoboCup 2050.
Autonomous Robots, May 2024.

2
Shiqi Zhang, Piyush Khandelwal, and Peter Stone.
iCORPP: interleaved commonsense reasoning and probabilistic planning on robots.
Robotics and Autonomous Systems, 174, April 2024.

3
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.
A collective AI via lifelong learning and sharing at the edge.
Nature Machine Intelligence, 6, pages 251–64, March 2024.

4
Reuth Mirsky, Xuesu Xiao, Justin Hart, and Peter Stone.
Conflict avoidance in social navigation — a survey.
ACM Transactions on Human-Robot Interaction (THRI), 13:1, pages 1–36, March 2024.

5
W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, and Alessandro Allievi.
Models of human preference for learning reward functions.
Transactions on Machine Learning Research (TMLR), 2024.

6
Yulin Zhang, William Macke, Jiaxun Cui, Sharon Hornstein, Daniel Urieli, and Peter Stone.
Learning a robust multiagent driving policy for traffic congestion reduction.
Neural Computing and Applications, November 2023.

7
Ori Ossmy, Danyang Han, Patrick MacAlpine, Justine Hoch, Peter Stone, and Karen E. Adolph.
Walking and falling: Using robot simulations to model the role of errors in infant walking.
Developmental Science, 27:2, e13449, September 2023.

8
Peter R. Wurman, Peter Stone, and Michael Spranger.
Improving artificial intelligence with games.
Science, 381:147–8, July 2023.

9
Keya Ghonasgi, Reuth Mirsky, Nisha Bhargava, Adrian M Haith, Peter Stone, and Ashish D Deshpande.
Kinematic coordinations capture learning during human-exoskeleton interaction.
Scientific Reports, 13:10322, June 2023.

10
Varun Kompella, Thomas Walsh, Samuel Barrett, Peter Wurman, and Peter Stone.
Event tables for efficient experience replay.
Transactions on Machine Learning Research (TMLR), 2023.

11
Xiaohan Zhang, Saeid Amiri, Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
Multimodal embodied attribute learning by robots for object-centric action policies.
Autonomous Robots, March 2023.

12
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, Erik Learned-Miller Dhireesha Kudithipudi, Seungwon Lee, Michael L. Littman, Jorge A. Mendez Sandeep Madireddy, 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.
A domain-agnostic approach for characterization of lifelong learning systems.
Neural Networks, pages 274–96, March 2023.

13
W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, and Peter Stone.
Reward (mis)design for autonomous driving.
Artificial Intelligence (AIJ), 316:103829, 2023.

14
Haresh Karnan, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Soren Pirk, Alexander Toshev, Justin Hart, Joydeep Biswas, and Peter Stone.
Socially compliant navigation dataset (SCAND): A large-scale dataset of demonstrations for social navigation.
Robotics and Automation Letters (RA-L), 7:11807–14, presented at International Conference on Intelligent Robots and Systems (IROS), October 2022.

15
Kingsley Nweye, Bo Liu, Nagy Zoltan, and Peter Stone.
Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings.
Journal of Energy and AI, September 2022.

16
Xuesu Xiao, Zizhao Wang, Zifan Xu, Bo Liu, abd Gauraang Dhamankar, Anirudh Nair, Garrett Warnell, and Peter Stone.
APPL: Adaptive planner parameter learning.
Robotics and Autonomous Systems (RAS), May 2022.

17
Yifeng Zhu, Peter Stone, and Yuke Zhu.
Bottom-up skill discovery from unsegmented demonstrations for long-horizon robot manipulation.
IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.

18
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone.
Motion planning and control for mobile robot navigation using machine learning: a survey.
Autonomous Robots, 46(5):569–97, March 2022.

19
Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Varun Kompella, Piyush Khandelwal, HaoChih Lin, Patrick MacAlpine, Declan Oller, Craig Sherstan, Takuma Seno, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead, Peter Duerr, Peter Stone, Michael Spranger, , and Hiroaki Kitano.
Outracing champion gran turismo drivers with deep reinforcement learning.
Nature, 62:223–28, Feb. 2022.

20
Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone.
Apple: Adaptive planner parameter learning from evaluative feedback.
IEEE Robotics and Automation Letters (RA-L), presented at International Conference on Intelligent Robots and Systems (IROS), October 2021.

21
Xuesu Xiao, Joydeep Biswas, and Peter Stone.
Learning inverse kinodynamics for accurate high-speed off-road navigation on unstructured terrain.
IEEE Robotics and Automation Letters (RA-L), presented at International Conference on Robotics and Automation(ICRA), July 2021.

22
Ruohan Zhang, Faraz Torabi, Garrett Warnell, and Peter Stone.
Recent advances in leveraging human guidance for sequential decision-making tasks.
Autonomous Agents and Multi-Agent Systems (JAAMAS), 35:31, June 2021.

23
Josiah P. Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, and Peter Stone.
Grounded action transformation for sim-to-real reinforcement learning.
Machine Learning (MLJ), May 2021.
Special Issue on Reinforcement Learning for Real Life.

24
Roberto Capobianco, Varun Kompella, James Ault, Guni Sharon, Stacy Jong, Spencer Fox, Lauren Meyers, Peter R. Wurman, and Peter Stone.
Agent-based markov modeling for improved COVID-19 mitigation policies.
The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
Based in part on earlier version in Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021.

25
Josiah P. Hanna, Scott Niekum, and Peter Stone.
Importance sampling in reinforcement learning with an estimated behavior policy.
Machine Learning (MLJ), 110:1267–1317, May 2021.

26
Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor.
Lucid dreaming for experience replay: Refreshing past states with the current policy.
Neural Computing and Applications, May 2021.

27
Bo Liu, Xuesu Xiao, and Peter Stone.
A lifelong learning approach to mobile robot navigation.
IEEE Robotics and Automation Letters (RA-L), presented at International Conference on Robotics and Automation (ICRA), 6(2), April 2021.

28
Alec Koppel, Garrett Warnell, Ethan Stump, Peter Stone, and Alejandro Ribeiro.
Policy evaluation in continuous MDPs with efficient kernelized gradient temporal difference.
IEEE Transactions on Automatic Control, April 2021.

29
Michael Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
Mechanism design for correlated valuations: efficient methods for revenue maximization.
Operations Research, March 2021.

30
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone.
Toward agile maneuvers in highly constrained spaces: Learning from hallucination.
IEEE Robotics and Automation Letters (RA-L), January 2021.

31
Shih-Yun Lo, Shiqi Zhang, and Peter Stone.
The PETLON algorithm to plan efficiently for task-level-optimal navigation.
Journal of Artificial Intelligence Research (JAIR), 69:471–520, October 2020.
Based on earlier version in Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
Best Robotics Paper Award.

32
Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, and Peter Stone.
Curriculum learning for reinforcement learning domains: A framework and survey.
Journal of Machine Learning Research (JMLR), 21(181):1–50, 2020.

33
Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone.
RIDM: Reinforced inverse dynamics modeling for learning from a single observed demonstration.
IEEE Robotics and Automation Letters (RA-L), presented at International Conference on Intelligent Robots and Systems (IROS), 5:6262–69, October 2020.

34
Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone.
APPLD: Adaptive planner parameter learning from demonstration.
IEEE Robotics and Automation Letters (RA-L), presented at International Conference on Intelligent Robots and Systems (IROS), June 2020.

35
Felipe Leno Da Silva, Garrett Warnell, Anna Helena Reali Costa, and Peter Stone.
Agents teaching agents: a survey on inter-agent transfer learning.
Autonomous Agents and Multi-Agent Systems (JAAMAS), Jan 2020.

36
Peter Stone.
A broader, more inclusive definition of AI.
Journal of Artificial General Intelligence (JAGI), 11(2):63–65, 2020.

37
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney.
Jointly improving parsing and perception for natural language commands through human-robot dialog.
The Journal of Artificial Intelligence Research (JAIR), 67, February 2020.

38
Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone.
The Right Music at the Right Time: Adaptive Personalized Playlists Based on Sequence Modeling.
MIS Quarterly, 43:3, pages 765–86, 2019.

39
Yuqian Jiang, Shi-qi Zhang, Piyush Khandelwal, and Peter Stone.
Task planning in robotics: an empirical comparison of PDDL- and ASP-based systems.
Frontiers of Information Technology & Electronic Engineering, April 2019.

40
Yuqian Jiang, Harel Yedidsion, Shiqi Zhang, Guni Sharon, and Peter Stone.
Multi-robot planning with conflicts and synergies.
Autonomous Robots, March 2019.

41
Ori Ossmy, Justine E. Hoch, Patrick MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
Variety wins: Soccer-playing robots and infant walking.
Frontiers in Neurorobotics, 12:19, 2018.

42
Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, and Antonio Liotta.
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.
Nature Communications, 9(2383), June 2018.

43
Stefano Albrecht and Peter Stone.
Autonomous agents modelling other agents: A comprehensive survey and open problems.
Artificial Intelligence (AIJ), 258:66–95, 2018.

44
Tarun Rambha, Stephen D. Boyles, Avinash Unnikrishnan, and Peter Stone.
Marginal cost pricing for system optimal traffic assignment with recourse under supply-side uncertainty.
Transportation Research Part B: Methodological, 110:104–21, 2018.

45
Patrick MacAlpine and Peter Stone.
Overlapping layered learning.
Artificial Intelligence (AIJ), 254:21–43, January 2018.

46
Guni Sharon, Michael W. Levin, Josiah P. Hanna, Tarun Rambha, Stephen D. Boyles, and Peter Stone.
Network-wide adaptive tolling for connected and automated vehicles.
Transportation Research Part C, 84:142–157, September 2017.

47
Corey White, Elad Liebman, and Peter Stone.
Decision mechanisms underlying mood-congruent emotional classification.
Cognition and Emotion, pages 1–10, 2017.

48
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.
BWIbots: A platform for bridging the gap between ai and human–robot interaction research.
The International Journal of Robotics Research (IJRR), 2017.

49
Stefano Albrecht, Somchaya Liemhetcharat, and Peter Stone.
Special issue on multiagent interaction without prior coordination: Guest editorial.
Autonomous Agents and Multi-Agent Systems (JAAMAS), 31:4, pages 765–66, July 2017.

50
Katie Genter, Tim Laue, and Peter Stone.
Three years of the robocup standard platform league drop-in player competition: Creating and maintaining a large scale ad hoc teamwork robotics competition.
Autonomous Agents and Multi-Agent Systems JAAMAS), pages 31:4, pages 790–820, July 2017.

51
Matteo Leonetti, Luca Iocchi, and Peter Stone.
A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
Artificial Intelligence (AIJ), 241:103 – 130, September 2016.

52
Samuel Barrett, Avi Rosenfeld, Sarit Kraus, and Peter Stone.
Making friends on the fly: Cooperating with new teammates.
Artificial Intelligence (AIJ), October 2016.

53
Matthew Hausknecht, Wen-Ke Li, Michael Mauk, and Peter Stone.
Machine learning capabilities of a simulated cerebellum.
IEEE Transactions on Neural Networks and Learning Systems, Jan 2016.

54
Katie Genter and Peter Stone.
Ad hoc teamwork behaviors for influencing a flock.
Acta Polytechnica, 56(1), 2016.

55
Elad Liebman, Benny Chor, and Peter Stone.
Representative selection in nonmetric datasets.
Applied Artificial Intelligence, 29:807–838, 2015.

56
Todd Hester and Peter Stone.
Intrinsically motivated model learning for developing curious robots.
Artificial Intelligence (AIJ), May 2015.

57
W. Bradley Knox and Peter Stone.
Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
Artificial Intelligence (AIJ), 225, August 2015.

58
Matthew Hausknecht, Joel Lehman, Risto Miikkulainen, and Peter Stone.
A neuroevolution approach to general atari game playing.
In IEEE Transactions on Computational Intelligence and AI in Games, 2013.

59
Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey R. Rosenschein, and Noa Agmon.
Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.
Artificial Intelligence (AIJ), 203:35–65, October 2013.

60
Doran Chakraborty and Peter Stone.
Multiagent learning in the presence of memory-bounded agents.
Autonomous Agents and Multiagent Systems (JAAMAS), 2013.

61
Todd Hester and Peter Stone.
TEXPLORE: Real-time sample-efficient reinforcement learning for robots.
Machine Learning (MLJ), 90(3), 2013.

62
Wen-Ke Li, Matthew J. Hausknecht, Peter Stone, and Michael D. Mauk.
Using a million cell simulation of the cerebellum: Network scaling and task generality.
Neural Networks, November 2012.

63
W. Bradley Knox, Brian D. Glass, Bradley C. Love, W. Todd Maddox, and Peter Stone.
How humans teach agents: A new experimental perspective.
International Journal of Social Robotics (IJSR), 4:409–421, October 2012.

64
W. Bradley Knox, A. Ross Otto, Peter Stone, and Bradley Love.
The nature of belief-directed exploratory choice in human decision-making.
Frontiers in Psychology, 2(398), January 2012.

65
Shivaram Kalyanakrishnan and Peter Stone.
Characterizing reinforcement learning methods through parameterized learning problems.
Machine Learning (MLJ), 84(1):205–247, June 2011.

66
David Fajardo, Tsz-Chiu Au, Travis Waller, Peter Stone, and David Yang.
Automated intersection control: Performance of a future innovation versus current traffic signal control.
Transportation Research Record (TRR), 2259:223–32, 2012.

67
Tobias Jung, Daniel Polani, and Peter Stone.
Empowerment for continuous agent-environment systems.
Adaptive Behavior, 19(1):16–39, 2011.

68
David Pardoe, Peter Stone, Maytal Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak.
Adaptive auction mechanism design and the incorporation of prior knowledge.
INFORMS Journal on Computing, 22(3):353–370, Summer 2010.

69
Jonathan Wildstrom, Peter Stone, and Emmett Witchel.
Autonomous return on investment analysis of additional processing resources.
International Journal on Autonomic Computing, 1(3), 2010.

70
Matthew E. Taylor and Peter Stone.
Transfer learning for reinforcement learning domains: A survey.
Journal of Machine Learning Research (JMLR), 10(1):1633–1685, 2009.

71
Shimon Whiteson, Matthew E. Taylor, and Peter Stone.
Critical factors in the empirical performance of temporal difference and evolutionary methods for reinforcement learning.
Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS), 21(1):1–27, 2010.

72
Mohan Sridharan and Peter Stone.
Color learning and illumination invariance on mobile robots: A survey.
Robotics and Autonomous Systems (RAS) Journal, 57(6-7):629–44, June 2009.

73
Juhyun Lee, W. Bradley Knox, and Peter Stone.
Inter-classifier feedback for human-robot interaction in a domestic setting.
Journal of Physical Agents (JoPhA), 2(2):41–50, July 2008.
Special Issue on Human Interaction with Domestic Robots.

74
Patrick Beeson, Jack O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter Stone.
Multiagent interactions in urban driving.
Journal of Physical Agents (JoPhA), 2(1):15–30, March 2008.
Special issue on Multi-Robot Systems.

75
Kurt Dresner and Peter Stone.
A multiagent approach to autonomous intersection management.
Journal of Artificial Intelligence Research (JAIR), 31:591–656, March 2008.

76
Daniel Stronger and Peter Stone.
Polynomial regression with automated degree: A function approximator for autonomous agents.
International Journal on Artificial Intelligence Tools, 17(1):159–174, 2008.
Based on earlier version in The 18th IEEE International Conference on Tools with Artificial Intelligence, November 2006.
Nominee for Best Paper Award.

77
Matthew E. Taylor, Peter Stone, and Yaxin Liu.
Transfer learning via inter-task mappings for temporal difference learning.
Journal of Machine Learning Research (JMLR), 8(1):2125–2167, 2007.

78
Mohan Sridharan and Peter Stone.
Planning actions to enable color learning on a mobile robot.
International Journal of Information and Systems Sciences, 3(3):510–25, 2007.

79
Mohan Sridharan and Peter Stone.
Structure-Based Color Learning on a Mobile Robot under Changing Illumination.
Autonomous Robots, 23(3):161–182, 2007.

80
Peter Stone.
Multiagent learning is not the answer. it is the question.
Artificial Intelligence (AIJ), 171:402–405, 2007.

81
Shimon Whiteson, Matthew E. Taylor, and Peter Stone.
Empirical studies in action selection for reinforcement learning.
Adaptive Behavior, 15(1):33–50, 2007.

82
Peter Stone, Mohan Sridharan, Daniel Stronger, Gregory Kuhlmann, Nate Kohl, Peggy Fidelman, and Nicholas K. Jong.
From pixels to multi-robot decision-making: A study in uncertainty.
Robotics and Autonomous Systems (RAS), 54(11):933–43, November 2006.
Special issue on Planning Under Uncertainty in Robotics.

83
Daniel Stronger and Peter Stone.
Towards autonomous sensor and actuator model induction on a mobile robot.
Connection Science Journal (CSJ), 18(2):97–119, June 2006.
Special Issue on Developmental Robotics.
Based on “Simultaneous calibration of action and sensor models on a mobile robot.”
In IEEE International Conference on Robotics and Automation (ICRA), April 2005.

84
Shimon Whiteson and Peter Stone.
Evolutionary Function Approximation for Reinforcement Learning.
Journal of Machine Learning Research (JMLR), 7:877–917, May 2006.

85
Charles Lee Isbell Jr., Michael Kearns, Dave Kormann, Satinder Singh, and Peter Stone.
Cobot in LambdaMOO: an adaptive social statistics agent.
Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS),
13(3):327–354, November, 2006.
Based on “Cobot in LambdaMOO: A social statistics agent.”
In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI), pages 36–41, 2001.

86
Peter Stone, Richard S. Sutton, and Gregory Kuhlmann.
Reinforcement learning for RoboCup-soccer keepaway.
Adaptive Behavior (AB), 13(2):165–188, 2005.
Based on “Scaling reinforcement learning toward RoboCup soccer.”
In Proceedings of the Eighteenth International Conference on Machine Learning (ICML), 2001.

87
Shimon Whiteson, Nate Kohl, Risto Miikkulainen, and Peter Stone.
Evolving keepaway soccer players through task decomposition.
Machine Learning (MLJ), 59(1):5–30, May 2005.
Based on earlier version in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), July 2003.

88
Michael Littman and Peter Stone.
A Polynomial-time Nash Equilibrium Algorithm for Repeated Games.
Decision Support Systems (DSS), 39:55–66, 2005.
Based on earlier version in Proceedings of the fourth annual ACM Conference on Electronic Commerce (EC), June 2003.

89
Peter Stone and Amy Greenwald.
The first international trading agent competition: Autonomous bidding agents.
Electronic Commerce Research (EC), 5(2):229–65, April 2005.

90
Shimon Whiteson and Peter Stone.
Towards autonomic computing: Adaptive job routing and scheduling.
Engineering Applications of Artificial Intelligence special issue on Autonomic Computing and Automation (EAAI), 17(7):855–69, October 2004.
Based on earlier version in Proceedings of the Sixteenth Innovative Applications of AI Conference (IAAI), San Jose, CA, July 2004.

91
Elizabeth Sklar, Simon Parsons, and Peter Stone.
Using RoboCup in university-level computer science education.
Journal of Educational Resources in Computing (JERIC), 4:2, June 2004.
Special Issue on Robotics in Undergraduate Education, Part 1.

92
Peter Stone, Robert E. Schapire, Michael L. Littman, János A. Csirik, and David McAllester.
Decision-theoretic bidding based on learned density models in simultaneous, interacting auctions.
Journal of Artificial Intelligence Research (JAIR), 19:209–242, September 2003.

93
Itsuki Noda and Peter Stone.
The RoboCup soccer server and CMUnited clients: Implemented infrastructure for MAS research.
Autonomous Agents and Multi-Agent Systems (JAAMAS), 7(1–2):101–120, July–September 2003.

94
Michael P. Wellman, Amy Greenwald, Peter Stone, and Peter R. Wurman.
The 2001 trading agent competition.
Electronic Markets (EM), 13(1):4–12, May 2003.

95
Peter Stone, Michael L. Littman, Satinder Singh, and Michael Kearns.
ATTac-2000: An adaptive autonomous bidding agent.
Journal of Artificial Intelligence Research (JAIR), 15:189–206, June 2001.
Based on earlier version in Proceedings of the Fifth International Conference on Autonomous Agents, 2001.

96
Peter Stone and Manuela Veloso.
Multiagent systems: A survey from a machine learning perspective.
Autonomous Robots, 8(3):345–383, July 2000.
Also in Tucker Balch and Lynne E. Parker, editors, Robot Teams: From Diversity to Polymorphism. AK Peters Ltd, 2002.

97
Michael Bowling, Manuela Veloso, and Peter Stone.
The CMUnited-98 champion small-robot team.
Advanced Robotics, 13(8):753–766, 2000.

98
Manuela Veloso, Peter Stone, and Kwun Han.
The CMUnited-97 robotic soccer team: Perception and multi-agent control.
Robotics and Autonomous Systems (RAS), 29(2-3):133–143, 2000.
Based on earlier version in Proceedings of the Second International Conference on Autonomous Agents, May 1998.

99
Peter Stone and Manuela Veloso.
Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork.
Artificial Intelligence (AIJ), 110(2):241–273, June 1999.

100
Peter Stone and Manuela Veloso.
A layered approach to learning client behaviors in the RoboCup soccer server.
Applied Artificial Intelligence (AAI), 12:165–188, 1998.

101
Minoru Asada, Yasuo Kuniyoshi, Alexis Drogoul, Hajime Asama, Maja Mataric, Dominique Duhaut, Peter Stone, and Hiroaki Kitano.
The RoboCup physical agent challenge: Phase-I.
Applied Artificial Intelligence (AAI), 12.2:251–263, March 1998.

102
Peter Stone and Manuela Veloso.
Towards collaborative and adversarial learning: A case study in robotic soccer.
International Journal of Human-Computer Studies (IJHCS), 48(1):83–104, January 1998.

103
Manuela Veloso and Peter Stone.
FLECS: Planning with a flexible commitment strategy.
Journal of Artificial Intelligence Research (JAIR), 3:25–52, June 1995.



Book Chapters

1
Sai Kiran Narayanaswami, Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit Narvekar, and Peter Stone.
Towards a real-time, low-resource, end-to-end object detection pipeline for robot soccer.
In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman, and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pages 62–74. Springer International Publishing, 2023.

2
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Eliott Fosong, William Macke, Mohan Sridharan, Peter Stone, and Stefano Albrecht.
A survey of ad hoc teamwork research.
In Dorothea Baumeister and Jörg Rothe, editors, Multi-Agent Systems, pages 275–93. Springer International Publishing, 2022.

3
Patrick MacAlpine, Bo Liu, William Macke, Caroline Wang, and Peter Stone.
UT Austin Villa: RoboCup 2021 3D simulation league competition champions.
In Rachid Alami, Joydeep Biswas, Maya Cakmak, and Oliver Obst editors, RoboCup 2021: Robot World Cup XXIV, Lecture Notes in Artificial Intelligence, pages 314–26. Springer, 2022.

4
Patrick MacAlpine, Faraz Torabi, Brahma Pavse, and Peter Stone.
UT Austin Villa: RoboCup 2019 3D simulation league competition and technical challenge champions.
In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn, and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pages 540–52. Springer, 2019.

5
Patrick MacAlpine, Faraz Torabi, Brahma Pavse, John Sigmon, and Peter Stone.
UT Austin Villa: RoboCup 2018 3D simulation league champions.
In Dirk Holz, Katie Genter, Maarouf Saad, and Oskar von Stryk, editors, RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pages 462–75. Springer, 2019.

6
Karl Tuyls and Peter Stone.
Multiagent learning paradigms.
In F. Belardinelli and E. Argente, editors, Multi-Agent Systems and Agreement Technologies, Volume 10767 of Lecture Notes in Artificial Intelligence, pages 1–19. Springer, 2018.

7
Patrick MacAlpine and Peter Stone.
UT Austin Villa: RoboCup 2017 3D simulation league competition and technical challenges champions.
In Claude Sammut, Oliver Obst, Flavio Tonidandel, and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, pages 473–85. Lecture Notes in Artificial Intelligence. Springer, 2018.

8
Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang and Peter Stone.
Fast and precise black and white ball detection for RoboCup soccer.
In Hidehisa Akyama, Oliver Obst, Claude Sammut, and Flavio Tonidandel, editors, RoboCup 2017: Robot Soccer World Cup XXI, pages 45–59. Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2018.
Nominee for Best Paper Award.

9
Patrick MacAlpine and Peter Stone.
Evaluating ad hoc teamwork performance in drop-in player challenges.
In Gita Sukthankar and Juan A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, volume 10642 of Lecture Notes in Artificial Intelligence, pages 168–86. Springer International Publishing, 2017.

10
Guni Sharon and Peter Stone.
A protocol for mixed autonomous and human-operated vehicles at intersections.
In Gita Sukthankar and Juan A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, volume 10642 of Lecture Notes in Artificial Intelligence, pages 151–67. Springer International Publishing, 2017.

11
Patrick MacAlpine and Peter Stone.
Prioritized role assignment for marking.
In Sven Behnke, Daniel D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, pages 306–18. Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2017.

12
Patrick MacAlpine and Peter Stone.
UT Austin Villa roboCup 3D simulation base code release.
In Sven Behnke, Daniel D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, pages 135–43. Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2017.

13
Patrick MacAlpine and Peter Stone.
UT Austin Villa RoboCup 3D simulation league competition.
In Sven Behnke, Daniel D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, pages 515–28. Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2017.

14
Kazunori Iwata, Elad Liebman, Peter Stone, Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii.
Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines.
In Roger Lee, editor, Computer and Information Science 2015, Studies in Computational Intelligence. Springer Verlag, Berlin, 2016.

15
Tsz-Chiu Au, Shun Zhang, and Peter Stone.
Autonomous intersection management for semi-autonomous vehicles.
In Handbook of Transportation. Routledge, 2016.

16
Patrick MacAlpine, Josiah Hanna, Jason Liang, and Peter Stone.
UT Austin Villa: RoboCup 2015 3D simulation league competition and technical challenges champions.
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.

17
David L. Leottau, Javier Ruiz del Solar, Patrick MacAlpine, and Peter Stone.
A study of layered learning strategies applied to individual behaviors in robot soccer.
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.

18
Patrick MacAlpine, Mike Depinet, Jason Liang, and Peter Stone.
UT Austin Villa: RoboCup 2014 3D simulation league competition and technical challenge champions.
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.

19
Mike Depinet, Patrick MacAlpine, and Peter Stone.
Keyframe sampling, optimization, and behavior integration: Towards long-distance kicking in the robocup 3d simulation league.
In H. Levent Akin, Reinaldo A. C. Bianchi, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2015.

20
Todd Hester and Peter Stone.
The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots
In RoboCup-2013: Robot Soccer World Cup XVII, 2014.

21
Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone.
The 2012 UT Austin Villa code release.
In RoboCup-2013: Robot Soccer World Cup XVII, 2014.

22
Noa Agmon, Daniel Urieli, and Peter Stone.
Ship Patrol: Multi Agent Patrol in Complex Environmental Conditions.
In Oren Gal, editor, Advanced in Marine Robotics, pages 37–62. LAP LAMBERT Academic Publishing, 2013.

23
Katie Genter, Noa Agmon, and Peter Stone.
Role-based ad hoc teamwork.
In Gita Sukthankar, Robert P. Goldman, Christopher Geib, David V. Pyhadath, and Hung Hai Bui, editors, Plan, Activity, and Intent Recognition: Theory and Practice, pages 251–272. Elsevier, Philadelphia, PA, USA, 2013.

24
Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone.
UT Austin Villa 2012: Standard platform league world champions.
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.

25
Patrick MacAlpine, Nick Collins, Adrian Lopez-Mobilia, and Peter Stone.
UT Austin Villa: RoboCup 2012 3D simulation league champion.
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.

26
Patrick MacAlpine, Francisco Barrera, and Peter Stone.
Positioning to win: A dynamic role assignment and formation positioning system.
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.

27
Aijun Bai, Xiaoping Chen, Patrick MacAlpine, Daniel Urieli, Samuel Barrett, and Peter Stone.
Wright Eagle and UT Austin Villa: RoboCup 2011 simulation league champions.
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.

28
Piyush Khandelwal and Peter Stone.
A low cost ground truth detection system for RoboCup.
In T. Roefer, N.M. Mayer, J. Savage, and U. Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence. Springer Verlag, 2012.

29
Todd Hester and Peter Stone.
The use of models.
in Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer Verlag, 2011.

30
Matthew Hausknecht and Peter Stone.
Learning powerful kicks on the aibo ers-7: The quest for a striker.
In Javier Ruiz-del-Solar, Eric Chown and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, pages 254–65. Lecture Notes in Artificial Intelligence. Springer Verlag, 2011.

31
Peter Stone, Michael Quinlan, and Todd Hester.
Can robots play soccer?
In Ted Richards, editor, Soccer and Philosophy: Beautiful Thoughts on the Beautiful Game, volume 51 of Popular Culture and Philosophy, pages 75–88. Open Court Publishing Company, 2010.

32
Itsuki Noda, Peter Stone, Tomohisa Yamashita, and Koichi Kurumatani.
Multi-Agent Social Simulation.
In Nakashima, H., Aghajan, H., & Augusto, J. C., editor, Handbook of Ambient Intelligence and Smart Environments, pages 703–729. 2010.

33
Peter Stone, Gal A. Kaminka, and Jeffrey S. Rosenschein.
Leading a best-response teammate in an ad hoc team.
In Esther David, Enrico Gerding, David Sarne, and Onn Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets, pages 132–146, November 2010.

34
David Pardoe and Peter Stone.
The 2007 TAC SCM prediction challenge.
In Wolfgang Ketter, Han La Poutré, Norman Sadeh, Onn Shehory, and William Walsh, editors, Agent-Mediated Electronic Commerce and Trading Agent Design and Alaysis, volume 44 of Lecture Notes in Business Information Processing (LNBIP), pages 175–89. 2010.

35
Shivaram Kalyanakrishnan and Peter Stone.
Learning complementary multiagent behaviors: A case study.
In Proceedings of the RoboCup International Symposium 2009. Springer Verlag, 2009.
Best Student Paper Award.

36
Shivaram Kalyanakrishnan, Todd Hester, Michael Quinlan, Yinon Bentor, and Peter Stone.
Three humanoid soccer platforms: Comparison and synthesis.
In Proceedings of the RoboCup International Symposium 2009. Springer Verlag, 2009.

37
Kurt Dresner, Mark VanMiddlesworth, and Peter Stone.
An unmanaged intersection protocol and improved intersection safety for autonomous vehicles.
In Ana L. C. Bazzan and Franziska Klugl, editors, Multi-Agent System for Traffic and Traffic Engineering, pages 193–217. IGI Global, Hershey, PA, 2009.

38
W. Bradley Knox, Juhyun Lee, and Peter Stone.
Domestic interaction on a segway base.
In Luca Iocchi, Hitoshi Matsubara, Alfredo Weitzenfeld, and Changjiu Zhou, editors, RoboCup-2008: Robot Soccer World Cup XII, Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2008.

39
David Pardoe and Peter Stone.
An autonomous agent for supply chain management.
In Gedas Adomavicius and Alok Gupta, editors, Handbooks in Information Systems Series: Business Computing. Elsevier, 2007.

40
David Pardoe and Peter Stone.
Adapting price predictions in TAC SCM.
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, volume 13 of Lecture Notes in Business Information Processing, pages 30–45. 2009.

41
Mazda Ahmadi and Peter Stone.
Instance-based action models for fast action planning.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI. Springer Verlag, Berlin, 2008.
Best Paper Award.

42
Shivaram Kalyanakrishnan, Peter Stone, and Yaxin Liu.
Model-based reinforcement learning in a complex domain.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI. Springer Verlag, Berlin, 2008.

43
Uli Grasemann, Daniel Stronger, and Peter Stone.
A neural network-based approach to robot motion control.
In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI. Springer Verlag, Berlin, 2008.

44
Daniel Stronger and Peter Stone.
Selective visual attention for object detection on a legged robot.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, pages 158–170. Volume 4434, Springer Verlag, Berlin, 2007.

45
Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone.
Half field offense in RoboCup soccer: A multiagent reinforcement learning case study.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, pages 72–85. Volume 4434, Springer Verlag, Berlin, 2007.
Best Student Paper Award.

46
Mohan Sridharan and Peter Stone.
Autonomous planned color learning on a legged robot.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, pages 270–278. Volume 4434, Springer Verlag, Berlin, 2007.

47
Peggy Fidelman and Peter Stone.
The chin pinch: A case study in skill learning on a legged robot.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, pages 59–71. Volume 4434, Springer Verlag, Berlin, 2007.

48
Manish Saggar, Thomas D'Silva, Nate Kohl, and Peter Stone.
Autonomous learning of stable quadruped locomotion.
In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, pages 98–109. Volume 4434, Springer Verlag, Berlin, 2007.
Nominee for Best Paper Award.

49
Kurt Dresner and Peter Stone.
Multiagent traffic management: Opportunities for multiagent learning.
In K. Tuyls et al., editor, LAMAS 2005, volume 3898 of Lecture Notes in Artificial Intelligence, pages 129–138. Springer Verlag, Berlin, 2006.

50
Mohan Sridharan and Peter Stone.
Towards eliminating manual color calibration at RoboCup.
In Itsuki Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX, pages 673–81. Volume 4020, Springer Verlag, Berlin, 2006.

51
Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu.
Keepaway soccer: From machine learning testbed to benchmark.
In Itsuki Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX, pages 93–105. Volume 4020, Springer Verlag, Berlin, 2006.

52
David Pardoe and Peter Stone.
Bidding for customer orders in TAC SCM.
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), volume 3435 of Lecture Notes in Artificial Intelligence, pages 143–157. Springer Verlag, Berlin, 2005.

53
Alexander A. Sherstov and Peter Stone.
Three automated stock-trading agents: A comparative study.
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), volume 3435 of Lecture Notes in Artificial Intelligence, pages 173–187. Springer Verlag, Berlin, 2005.

54
Alexander A. Sherstov and Peter Stone.
Function approximation via tile coding: Automating parameter choice.
In J.-D. Zucker and I. Saitta, editors, SARA 2005, volume 3607 of Lecture Notes in Artificial Intelligence, pages 194–205, Berlin, 2005. Springer Verlag.

55
Daniel Stronger and Peter Stone.
A model-based approach to robot joint control.
In Daniele Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, volume 3276 of Lecture Notes in Artificial Intelligence, pages 297–309. Springer Verlag, Berlin, 2005.

56
Gregory Kuhlmann, Peter Stone, and Justin Lallinger.
The UT Austin Villa 2003 champion simulator coach: A machine learning approach.
In Daniele Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, volume 3276 of Lecture Notes in Artificial Intelligence, pages 636–644. Springer Verlag, Berlin, 2005.

57
Mohan Sridharan and Peter Stone.
Towards illumination invariance in the legged league.
In Daniele Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, volume 3276 of Lecture Notes in Artificial Intelligence, pages 196–208. Springer Verlag, Berlin, 2005.

58
Yi Feng, Ronggang Yu, and Peter Stone.
Two stock-trading agents: Market making and technical analysis.
In Agent Mediated Electronic Commerce V: Designing Mechanisms and Systems. Lecture Notes in Artificial Intelligence. Springer Verlag, 2004.

59
Peter Stone.
RoboCup as an introduction to CS research.
In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, RoboCup-2003: Robot Soccer World Cup VII, volume 3020 of Lecture Notes in Artificial Intelligence, pages 284–95. Springer Verlag, Berlin, 2004.

60
Peter Stone.
Multiagent competitions and research: Lessons from RoboCup and TAC.
In Gal A. Kaminka, Pedro U. Lima, and Raul Rojas, editors, RoboCup-2002: Robot Soccer World Cup VI, volume 2752 of Lecture Notes in Artificial Intelligence, pages 224–237. Springer Verlag, Berlin, 2003.

61
Peter Stone, Robert E. Schapire, János A. Csirik, Michael L. Littman, and David McAllester.
ATTac-2001: A learning, autonomous bidding agent.
In Agent Mediated Electronic Commerce IV: Designing Mechanisms and Systems, pages 143–160. Volume 2531 of Lecture Notes in Artificial Intelligence. Springer Verlag, 2002.

62
Paul S. A. Reitsma, Peter Stone, János A. Csirik, and Michael L. Littman.
Self-enforcing strategic demand reduction.
In Agent Mediated Electronic Commerce IV: Designing Mechanisms and Systems, pages 289–306. Volume 2531 of Lecture Notes in Artificial Intelligence. Springer Verlag, 2002.

63
Peter Stone and Richard S. Sutton.
Keepaway soccer: a machine learning testbed.
In Andreas Birk, Silvia Coradeschi, and Satoshi Tadokoro, editors, RoboCup-2001: Robot Soccer World Cup V, volume 2377 of Lecture Notes in Artificial Intelligence, pages 214–223. Springer Verlag, Berlin, 2002.

64
Peter Stone, Richard S. Sutton, and Satinder Singh.
Reinforcement learning for 3 vs. 2 keepaway.
In Peter Stone, Tucker Balch, and Gerhard Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, volume 2019 of Lecture Notes in Artificial Intelligence, pages 249–258. Springer Verlag, Berlin, 2001.

65
David McAllester and Peter Stone.
Keeping the ball from CMUnited-99.
In Peter Stone, Tucker Balch, and Gerhard Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, volume 2019 of Lecture Notes in Artificial Intelligence, pages 333–338. Springer Verlag, Berlin, 2001.

66
Peter Stone and Manuela Veloso.
Layered learning.
In Ramon López de Mántaras and Enric Plaza, editors, Machine Learning: ECML 2000, pages 369–381. Springer Verlag, Barcelona,Catalonia,Spain, May/June 2000.
Proceedings of the Eleventh European Conference on Machine Learning (ECML-2000).

67
Peter Stone and Manuela Veloso.
Layered learning and flexible teamwork in RoboCup simulation agents.
In M. Veloso, E. Pagello, and H. Kitano, editors, RoboCup-99: Robot Soccer World Cup III, volume 1856 of Lecture Notes in Artificial Intelligence, pages 495–508. Springer Verlag, Berlin, 2000.

68
Peter Stone and Manuela Veloso.
Task decomposition and dynamic role assignment for real-time strategic teamwork.
In J. P. Müller, M. P. Singh, and A. S. Rao, editors, Intelligent Agents V — Proceedings of the Fifth International Workshop on Agent Theories, Architectures, and Languages (ATAL-98), pages 293–308. Springer-Verlag, Heidelberg, 1999.

69
Peter Stone and Manuela Veloso.
Team-partitioned, opaque-transition reinforcement learning.
In Minoru Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer World Cup II, volume 1604 of Lecture Notes in Artificial Intelligence, pages 261–72. Springer Verlag, Berlin, 1999.
Also in Proceedings of the Third International Conference on Autonomous Agents,1999.

70
Peter Stone and Manuela Veloso.
Communication in domains with unreliable, single-channel, low-bandwidth communication.
In Alexis Drogoul, Milind Tambe, and Toshio Fukuda, editors, Collective Robotics, pages 85–97. Springer Verlag, Berlin, July 1998.

71
Peter Stone and Manuela Veloso.
Using decision tree confidence factors for multiagent control.
In Hiroaki Kitano, editor, RoboCup-97: Robot Soccer World Cup I, volume 1395 of Lecture Notes in Artificial Intelligence, pages 99–111. Springer Verlag, Berlin, 1998.
Also in Proceedings of the Second International Conference on Autonomous Agents, 1998.

72
Peter Stone and Manuela Veloso.
User-guided interleaving of planning and execution.
In M. Ghallab and A. Milani, editors, New Directions in AI Planning, pages 103–112. IOS Press, 1996.



Refereed Conference Papers

1
Caroline Wang, Arrasy Rahman, Ishan Durugkar, Elad Liebman, and Peter Stone.
N-agent ad hoc teamwork.
In Conference on Neural Information Processing Systems (NeurIPS), December 2024.

2
Borja G. Leon, Francesco Riccio, Kaushik Subramanian, Peter R. Wurman, and Peter Stone.
Discovering creative behaviors through DUPLEX: diverse universal features for policy exploration.
In Conference on Neural Information Processing Systems (NeurIPS), December 2024.

3
Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martin-Martin, Amy Zhang, Scott Niekum, and Peter Stone.
SkiLD: unsupervised skill discovery guided by local dependencies.
In Conference on Neural Information Processing Systems (NeurIPS), December 2024.

4
Jiaheng Hu, Zizhao Wang, Roberto Martín-Martín, and Peter Stone.
Disentangled unsupervised skill discovery for efficient hierarchical reinforcement learning.
In Conference on Neural Information Processing Systems (NeurIPS), December 2024.

5
Shivin Dass, Jiaheng Hu, Ben Abbatematteo, Peter Stone, and Roberto Martín-Martín.
Learning to look: Seeking information for decision making via policy factorization.
In Conference on Robot Learning (CoRL), November 2024.

6
Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Peter Stone, and Yanjun Qi.
LaRS: Latent Reasoning Skill for Chain-of-Thought Reasoning.
In Conference on Empirical Methods in Natural Language Processing (EMNLP), November 2024.

7
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi, Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin Hart.
Dobby: A conversational service robot driven by gpt-4.
In International Symposium on Robot and Human Interactive Communication (RO-MAN), August 2024.

8
Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, and Peter Stone.
A super-human vision-based reinforcement learning agent for autonomous racing in Gran Turismo.
In Reinforcement Learning Conference (RLC), August 2024.
Outstanding Paper Award on Applications of RL.

9
Alexander Levine, Peter Stone, and Amy Zhang.
Multistep inverse is not all you need.
In Reinforcement Learning Conference (RLC), August 2024.

10
William Yue, Bo Liu, and Peter Stone.
t-DGR: A trajectory-based deep generative replay method for continual learning in decision making.
In Conference on Lifelong Learning Agents (CoLLAs), July 2024.

11
Catherine Weaver, Roberto Capobianco, Peter Wurman, Peter Stone, and Masayoshi Tomizuka.
Real-time trajectory generation via dynamic movement primitives for autonomous racing.
In American Control Conference (ACC). IEEE, July 2024.

12
Amir Hossain Raj, Zichao Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep Biswas, , and Xuesu Xiao.
Rethinking social robot navigation: Leveraging the best of two worlds.
In International Conference on Robotics and Automation (ICRA), May 2024.

13
Haresh, Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
Wait, that feels familiar: Learning to extrapolate human preferences for preference-aligned path planning.
In International Conference on Robotics and Automation (ICRA), May 2024.

14
Yoonchang Sung, Rahul Shome, and Peter Stone.
Asynchronous task plan refinement for multi-robot task and motion planning.
In IEEE International Conference on Robotics and Automation (ICRA), May 2024.

15
Zifan Xu, Amir Hossain Raj, Xuesu Xiao, and Peter Stone.
Dexterous legged locomotion in confined 3d spaces with reinforcement learning.
In IEEE International Conference on Robotics and Automation (ICRA), May 2024.

16
Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, and Ambuj Tewari.
Sample efficient myopic exploration through multitask reinforcement learning with diverse tasks.
In International Conference on Learning Representations (ICLR), May 2024.

17
Shahaf S. Shperberg, Bo Liu, and Peter Stone.
Relaxed exploration constrained reinforcement learning.
In Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024.

18
Arrasy Rahman, Jiaxun Cui, and Peter Stone.
Minimum coverage sets for training robust ad hoc teamwork agents.
In The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), February 2024.

19
Zizhao Wang, Caroline Wang, Xuesu Xiao, Yuke Zhu, and Peter Stone.
Building minimal and reusable causal state abstractions for reinforcement learning.
In The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), February 2024.

20
W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter Stone, and Scott Niekum.
Learning optimal advantage from preferences and mistaking it for reward.
In The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), February 2024.

21
Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
Fast adaptive multitask optimization.
In Conference on Neural Information Processing Systems (NeurIPS), December 2023.

22
Siddhant Agarwal, Ishan Durugkar, Peter Stone, and Amy Zhang.
f-policy gradients: A general framework for goal conditioned rl using f-divergences.
In Conference on Neural Information Processing Systems, December 2023.

23
Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, and Peter Stone.
LIBERO: Benchmarking knowledge transfer in lifelong robot learning.
In 37th Conference on Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, December 2023.

24
Swathi Mannem, William Macke, Peter Stone, and Reuth Mirsky.
Exploring the cost of interruptions in human-robot teaming.
In IEEE-RAS Humanoids, December 2023.

25
Zizhao Wang, Jiaheng Hu, Peter Stone, and Roberto Martín-Martín.
Elden: Exploration via local dependencies.
In Conference on Neural Information Processing Systems, December 2023.

26
Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
FAMO: Fast Adaptive Multitask Optimization.
In Conference on Neural Information Processing Systems, December 2023.

27
Yifeng Zhu, Zhenyu Jiang, Peter Stone, and Yuke Zhu.
Learning generalizable manipulation policies with object-centric 3D representations.
In Proceedings of the 6th Conference on Robot Learning (CoRL), November 2023.

28
Haresh Karnan, Elvin Yang, Daniel Furkash, Garrett Warnell, Joydeep Biswas, and Peter Stone.
STERLING: Self-supervised terrain representation learning from unconstrained robot experience.
In Proceedings of the 6th Conference on Robot Learning (CoRL), November 2023.

29
Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu, Peter Stone, and Shiqi Zhang.
Symbolic state space optimization for long horizon mobile manipulation planning.
In International Conference on Intelligent Robots and Systems (IROS), October 2023.

30
Keya Ghonasgi, Reuth Mirsky, Adrian M. Haith, Peter Stone, and Ashish Deshpande.
A novel control law for multi-joint human-robot interaction tasks while maintaining postural coordination.
In International Conference on Intelligent Robots and Systems (IROS), October 2023.

31
Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, and Peter Stone.
Model-based meta automatic curriculum learning.
In The Second Conference on Lifelong Learning Agents (CoLLAs), August 2023.

32
Dustin Morrill, Thomas J. Walsh, Daniel Hernandez, Peter R. Wurman, and Peter Stone.
Composing efficient, robust tests for policy selection.
In The 39th Conference on Uncertainty in Artificial Intelligence (UAI), August 2023.

33
Jiaheng Hu, Peter Stone, and Roberto Martin-Martin.
Causal policy gradient for whole-body mobile manipulation.
In Robotics: Science and Systems (RSS), July 2023.

34
Yoonchang Sung and Peter Stone.
Motion planning (in)feasibility detection using a prior roadmap via path and cut search.
In Robotics: Science and Systems (RSS), July 2023.

35
Vaibhav Bajaj, Guni Sharon, and Peter Stone.
Task phasing: Automated curriculum learning from demonstrations.
In Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS), July 2023.

36
Caroline Wang, Garrett Warnell, and Peter Stone.
D-shape: Demonstration-shaped reinforcement learning via goal conditioning.
In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2023.

37
Shahaf S. Shperberg, Bo Liu, and Peter Stone.
Relaxed exploration constrained reinforcement learning.
In International Conference on Autonomous Agents and Multiagent Systems, May 2023.

38
Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, and Yuandong Tian.
Macta: A multi-agent reinforcement learning approach for cache timing attacks and detection.
In The Eleventh International Conference on Learning Representations (ICLR), May 2023.

39
Jinsoo Park, Xuesu Xiao, Garrett Warnell, Harel Yedidsion, and Peter Stone.
Learning perceptual hallucination for multi-robot navigation in narrow hallways.
In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA), May 2023.

40
Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, and Peter Stone.
Benchmarking reinforcement learning techniques for autonomous navigation.
In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA), May 2023.

41
Caroline Wang, Ishan Durugkar, Elad Liebman, and Peter Stone.
Dm$^2$: Decentralized multi-agent reinforcement learning via distribution matching.
In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), February 2023.

42
Serena Booth, W Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, and Alessandro Allievi.
The perils of trial-and-error reward design: Misdesign through overfitting and invalid task specifications.
In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Feb 2023.

43
Bo Liu, Yihao Feng, Qiang Liu, and Peter Stone.
Metric residual networks for sample efficient goal-conditioned reinforcement learning.
In Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), Februray 2023.

44
Yifeng Zhu, Abhishek Joshi, Peter Stone, and Yuke Zhu.
VIOLA: Object-centric imitation learning for vision-based robot manipulation.
In Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022.

45
Yoonchang Sung, Zizhao Wang, and Peter Stone.
Learning to correct mistakes: Backjumping in long-horizon task and motion planning.
In Proceedings of the 6th Conference on Robot Learning (CoRL), December 2022.

46
James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherston, Peter R. Wurman, and Peter Stone.
Value function decomposition for iterative design of reinforcement learning agents.
In Conference on Neural Information Processing Systems (NeurIPS), December 2022.

47
Mao Ye, Bo Liu, Stephen Wright, and Peter Stone.
BOME! Bilevel optimization made easy: A simple first-order approach.
In Conference on Neural Information Processing Systems (NeurIPS), December 2022.

48
Keya Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter Stone, and Ashish D Deshpande.
Quantifying changes in kinematic behavior of a human-exoskeleton interactive system.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2022.

49
Haresh Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett Warnell, Peter Stone, and Joydeep Biswas.
VI-IKD: High-speed accurate off-road navigation using learned visual-inertial inverse kinodynamics.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2022.

50
Shahaf Shperberg, Bo Liu, Allessandro Allievi, and Peter Stone.
A rule-based shield: Accumulating safety rules from catastrophic action effects.
In Proceedings of the 1st Conference on Lifelong Learning Agents (CoLLA), August 2022.

51
Bo Liu, Qiang Liu, and Peter Stone.
Continual learning and private unlearning.
In Proceedings of the 1st Conference on Lifelong Learning Agents (CoLLA), August 2022.

52
Akarsh Kumar, Bo Liu, Risto Miikkulainen, and Peter Stone.
Effective mutation rate adaptation through group elite selection.
In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), July 2022.

53
Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, and Peter Stone.
Causal dynamics learning for task-independent state abstraction.
In Proceedings of the 39th International Conference on Machine Learning (ICML), July 2022.

54
Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, and Peter Stone.
Dynamic sparse training for deep reinforcement learning.
In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), July 2022.
Based on earlier version in AAMAS workshop on Adaptive Learning Agents (ALA), May 2022.
Best Paper Award.

55
Jiaxun Cui, Hang Qiu, Dian Chen, Peter Stone, and Yuke Zhu.
Coopernaut: End-to-end driving with cooperative perception for networked vehicles.
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2022.

56
Haresh Karnan, Garrett Warnell, Xuesu Xiao, and Peter Stone.
VOILA: Visual-observation-only imitation learning for autonomous navigation.
In International Conference on Robotics and Automation (ICRA), May 2022.

57
Haresh Karnan, Garrett Warnell, Faraz Torabi, and Peter Stone.
Adversarial imitation learning from video using a state observer.
In International Conference on Robotics and Automation (ICRA), May 2022.

58
Eddy Hudson, Garrett Warnell, Faraz Torabi, and Peter Stone.
Skeletal feature compensation for imitation learning with embodiment mismatch.
In International Conference on Robotics and Automation (ICRA), May 2022.

59
Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuke Zhu, Peter Stone, and Shiqi Zhang.
Visually grounded task and motion planning for mobile manipulation.
In International Conference on Robotics and Automation (ICRA), May 2022.

60
Ishan Durugkar, Mauricio Tec, Scott Niekum, and Peter Stone.
Adversarial Intrinsic Motivation for Reinforcement Learning.
In Conference on Neural Information Processing Systems (NeurIPS), December 2021.

61
Bo Liu, Xingchao Liu, Peter Stone, and Qiang Liu.
Conflict-averse gradient descent for multi-task learning.
In Conference on Neural Information Processing Systems (NeurIPS), December 2021.

62
Sihang Guo, Ruohan Zhang, Bo Liu, Yifeng Zhu, Dana Ballard, Mary Hayhoe, and Peter Stone.
Machine versus human attention in deep reinforcement learning tasks.
In Conference on Neural Information Processing Systems (NeurIPS), December 2021.

63
Faraz Torabi, Garrett Warnell, and Peter Stone.
Dealio: Data-efficient adversarial learning for imitation from observation.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2021.

64
Keya Ghonasgi, Reuth Mirsky, Sanmit Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D. Deshpande.
Capturing skill state in curriculum learning for human skill acquisition.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2021.

65
Zizhao Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
From agile ground to aerial navigation: Learning from learned hallucination.
In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), October 2021.

66
Bo Liu, Xuesu Xiao, and Peter Stone.
Team orienteering coverage planning with uncertain reward.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2021.

67
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, and Animashree Anandkumar.
Coach-player multi-agent reinforcement learning for dynamic team composition.
In Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021 (ICML), July 2021.

68
Shih-Yun Lo, Benito R. Fernandez, Peter Stone, and Andrea Lockerd Thomaz.
Towards Safe Motion Planning in Human Workspaces: A Robust Multi-agent Approach.
In Proceedings of the International Conference on Robotics and Automation (ICRA), June 2021.

69
Blake Holman, Abrar Anwar, Akash Singh, Mauricio Tec, Justin Hart, and Peter Stone.
Watch where you're going! gaze and head orientation as predictors for social robot navigation.
In Proceedings of the International Conference on Robotics and Automation (ICRA), June 2021.

70
Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone.
APPLI: Adaptive planner parameter learning from interventions.
In Proceedings of the International Conference on Robotics and Automation (ICRA), June 2021.

71
Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, and Peter Stone.
APPLR: Adaptive planner parameter learning from reinforcement.
In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA), June 2021.

72
Piyush Khandelwal, James MacGlashan, Peter Wurman, and Peter Stone.
Efficient real-time inference in temporal convolution networks.
In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA), June 2021.

73
Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter Stone.
A scavenger hunt for service robots.
In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA), June 2021.

74
Xuesu Xiao, Bo Liu, and Peter Stone.
Agile robot navigation through hallucinated learning and sober deployment.
In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA), June 2021.

75
Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone.
Scalable multiagent driving policies for reducing traffic congestion.
In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021.

76
Reuth Mirsky and Peter Stone.
The seeing-eye robot grand challenge: Rethinking automated care.
In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021.

77
Yu-Sian Jiang, Garrett Warnell, and Peter Stone.
Goal blending for responsive shared autonomy in a navigating vehicle.
In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), Feb 2021.

78
Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
Temporal-logic-based reward shaping for continuing reinforcement learning tasks.
In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), February 2021.

79
William Macke, Reuth Mirsky, and Peter Stone.
Expected value of communication for planning in ad hoc teamwork.
In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.

80
Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, and Peter Stone.
An imitation from observation approach to transfer learning with dynamics mismatch.
In Conference on Neural Information Processing Systems (NeurIPS), December 2020.

81
Lemeng Wu, Bo Liu, Qiang Liu, and Peter Stone.
Firefly steepest descent: a general approach for growing neural networks.
In Conference on Neural Information Processing Systems (NeurIPS), December 2020.

82
Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, and W. Bradley Knox.
The EMPATHIC framework for task learning from implicit human feedback.
In Proceedings of the 4th Conference on Robot Learning (CoRL), November 2020.

83
Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
Learning to improve multi-robot hallway navigation.
In Proceedings of the 4th Conference on Robot Learning (CoRL), November 2020.

84
Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone.
Using human-inspired signals to disambiguate navigational intentions.
In Proceedings of the International Conference on Social Robotics (ICSR), November 2020.

85
Rishi Shah, Yuqian Jiang, Justin Hart, and Peter Stone.
Deep r-learning for continual area sweeping.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020.

86
Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, and Peter Stone.
Stochastic grounded action transformation for robot learning in simulation.
In Proceedigs of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020.

87
Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone.
Reinforced grounded action transformation for sim-to-real transfer.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020.

88
Keting Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen.
Learning and reasoning for robot dialog and navigation tasks.
In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 107–117, 1st virtual meeting, July 2020. Association for Computational Linguistics.

89
Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone.
Reducing sampling error in batch temporal difference learning.
In Proceedings of the 37th International Conference on Machine Learning (ICML), July 2020.

90
Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, and Peter Stone.
A penny for your thoughts: The value of communication in ad hoc teamwork.
In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), July 2020.

91
Ishan Durugkar, Elad Liebman, and Peter Stone.
Balancing individual preferences and shared objectives in multiagent reinforcement learning.
In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), July 2020.

92
Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond Mooney.
Optimal use of verbal instructions for multi-robot human navigation guidance.
In International Conference on Social Robotics (ICSR), pages 133–143. Springer, November 2019.

93
Yuqian Jiang, Fangkai Yang, Shiqi Zhang, and Peter Stone.
Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019.

94
Felipe Leno Da Silva, Anna Helena Reali Costa, and Peter Stone.
Building self-play curricula online by playing with expert agents in adversarial games.
In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.

95
Shani Alkobi Manish Ravula and Peter Stone.
Ad hoc teamwork with behavior switching agents.
In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.

96
Faraz Torabi, Garrett Warnell, and Peter Stone.
Imitation learning from video by leveraging proprioception.
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.

97
Faraz Torabi, Garrett Warnell, and Peter Stone.
Recent advances in imitation learning from observation.
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.

98
Ruohan Zhang, Faraz Torabi, Lin Guan, Dana Ballard, and Peter Stone.
Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.

99
Josiah Hanna, Scott Niekum, and Peter Stone.
Importance sampling policy evaluation with an estimated behavior policy.
In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.

100
Yuqian Jiang, Nick Walker, Justin Hart, and Peter Stone.
Open-world reasoning for service robots.
In Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS), July 2019.

101
Josiah Hanna and Peter Stone.
Reducing sampling error in policy gradient learning.
In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.

102
Sanmit Narvekar and Peter Stone.
Learning curriculum policies for reinforcement learning.
In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.

103
Guni Sharon, Stephen D. Boyles, Shani Alkoby, and Peter Stone.
Marginal cost pricing with a fixed error factor in traffic networks.
In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.

104
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney.
Improving Grounded Natural Language Understanding through Human-Robot Dialog.
In IEEE International Conference on Robotics and Automation (ICRA), May 2019.

105
Josiah Hanna, Guni Sharon, Stephen Boyles, and Peter Stone.
Selecting compliant agents for opt-in micro-tolling.
In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), January 2019.

106
Aishwarya Padmakumar, Peter Stone, and Raymond J. Mooney.
Learning a policy for opportunistic active learning.
In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Brussels, Belgium, November 2018.

107
Justin W. Hart, Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter Stone.
PRISM: Pose registration for integrated semantic mapping.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2018.

108
Yu-Sian Jiang, Garrett Warnell, and Peter Stone.
Inferring user intention using gaze in vehicles.
In The 20th ACM International Conference on Multimodal Interaction (ICMI), October 2018.

109
Elad Liebman and Peter Stone.
On the impact of music on decision making in cooperative tasks
In Proceedings of the 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.

110
Rolando Fernandez, Nathan John, Sean Kirmani, Justin Hart, Jivko Sinapov, and Peter Stone.
Passive demonstrations of light-based robot signals for improved human interpretability.
In Proceedings of the 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.

111
Yu-Sian Jiang, Garrett Warnell, Eduardo Munera, and Peter Stone.
A study of human-robot copilot systems for en-route destination changing.
In Proceedings of the 27th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), August 2018.

112
Elad Liebman, Eric Zavesky, and Peter Stone.
A stitch in time - Autonomous model management via reinforcement learning.
In Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.

113
Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, and Peter Stone.
Multi-modal predicate identification using dynamically learned robot controllers.
In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), July 2018.

114
Faraz Torabi, Garrett Warnell, and Peter Stone.
Behavioral cloning from observation.
In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), July 2018.

115
Jesse Thomason, Jivko Sinapov, Raymond J. Mooney, and Peter Stone.
Guiding exploratory behaviors for multi-modal grounding of linguistic descriptions.
In Proceedings of the 32nd Conference on Artificial Intelligence (AAAI), February 2018.

116
Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
Dyetc: Dynamic electronic toll collection for traffic congestion alleviation.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), February 2018.

117
Guni Sharon, Michael Albert, Tarun Rambha, Stephen Boyles, and Peter Stone.
Traffic optimization for a mixture of self-interested and compliant agents.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), February 2018.

118
Garrett Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), February 2018.

119
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin Hart, Peter Stone, and Raymond J. Mooney.
Opportunistic active learning for grounding natural language descriptions.
In Sergey Levine, Vincent Vanhoucke, and Ken Goldberg, editors, Proceedings of the 1st Annual Conference on Robot Learning (CoRL), pages 67–76, Mountain View, California, November 2017. PMLR.

120
Dongcai Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen.
Leveraging commonsense reasoning and multimodal perception for robot spoken dialog systems.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2017.

121
Josiah Hanna, Philip Thomas, Peter Stone, and Scott Niekum.
Data-efficient policy evaluation through behavior policy search.
In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.

122
Sanmit Narvekar, Jivko Sinapov, and Peter Stone.
Autonomous task sequencing for customized curriculum design in reinforcement learning.
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August 2017.

123
Piyush Khandelwal and Peter Stone.
Multi-robot human guidance: Human experiments and multiple concurrent requests.
In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.

124
Guni Sharon, Josiah P. Hanna, Tarun Rambha, Michael W. Levin, Michael Albert, Stephen D. Boyles, and Peter Stone.
Real-time adaptive tolling scheme for optimized social welfare in traffic networks.
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.

125
Josiah Hanna, Peter Stone, and Scott Niekum.
Bootstrapping with models: Confidence intervals for off-policy evaluation.
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.

126
Shiqi Zhang, Yuqian Jiang, Guni Sharon, and Peter Stone.
Multirobot symbolic planning under temporal uncertainty.
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS), May 2017.

127
Michael Albert, Vincent Conitzer, and Peter Stone.
Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS), May 2017.

128
Stefano Albrecht and Peter Stone.
Reasoning about hypothetical agent behaviours and their parameters.
In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.

129
Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, and Peter Stone.
Designing better playlists with monte carlo tree search.
In Proceedings of the Twenty-Ninth Conference On Innovative Applications Of Artificial Intelligence (IAAI), February 2017.

130
Shiqi Zhang, Piyush Khandelwal, and Peter Stone.
Dynamically constructed (PO)MDPs for adaptive robot planning.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.

131
Michael Albert, Vincent Conitzer, and Peter Stone.
Automated Design of Robust Mechanisms.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.

132
Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, and Peter Stone.
Automatic curriculum graph generation for reinforcement learning agents.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.

133
Josiah Hanna and Peter Stone.
Grounded action transformation for robot learning in simulation.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.

134
Donghyun Kim, Steven Jens Jorgensen, Peter Stone, and Luis Sentis.
Dynamic behaviors on the NAO robot with closed-loop whole body operational space control.
In IEEE-RAS International Conference on Humanoid Robots, 2016.

135
Jesse Thomason, Jivko Sinapov, Max Svetlik, Peter Stone and Raymond Mooney.
Learning multi-modal grounded linguistic semantics by playing I, Spy.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2016.

136
Jivko Sinapov, Priyanka Khante, Maxwell Svetlik and Peter Stone.
Learning to order objects using haptic and proprioceptive exploratory behaviors.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2016.

137
Shiqi Zhang, Dongcai Lu, Xiaoping Chen, and Peter Stone.
Robot scavenger hunt: A standardized framework for evaluating intelligent mobile robots.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) — Demonstration Track, July 2016.

138
Elad Liebman, Peter Stone, and Corey N. White.
Impact of music on decision making in quantitative tasks.
In Proceedings of the 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.

139
Piyush Khandelwal, Elad Liebman, Scott Niekum, and Peter Stone.
On the analysis of complex backup strategies in Monte Carlo Tree Search.
In Proceedings of the 33rd International Conference on Machine Learning (ICML), June 2016.

140
Katie Genter and Peter Stone.
Adding influencing agents to a flock.
In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.

141
Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone.
Source task creation for curriculum learning.
In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.

142
Daniel Urieli and Peter Stone.
An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.

143
Matthew Hausknecht and Peter Stone.
Deep reinforcement learning in parameterized action space.
In Proceedings of the International Conference on Learning Representations (ICLR), May 2016.

144
Daniel Urieli and Peter Stone.
Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
In Proceedings of the 30th Conference on Artificial Intelligence (AAAI), February 2016.

145
Peter Stone.
What's hot at RoboCup (extended abstract).
In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), February 2016.

146
Ilaria Gori, Jivko Sinapov, Priyanka Khante, Peter Stone, and J.K. Aggarwal.
Robot-centric activity recognition “in the wild.”
In International Conference on Social Robotics (ICSR), October 2015.

147
Elad Liebman, Peter Stone, and Corey N. White.
How music alters decision making: Impact of music stimuli on emotional classification.
In Proceedings of the 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.

148
Katie Genter, Tim Laue, and Peter Stone.
Benchmarking robot cooperation without pre-coordination in the robocup standard platform league drop-in player competition.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2015.
Finalist for RoboCup Best Paper Award.

149
Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone.
Mobile robot planning using action language BC with an abstraction hierarchy.
In Proceedings of the 13th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR), September 2015.

150
Jesse Thomason, Shiqi Zhang, Raymond Mooney, and Peter Stone.
Learning to interpret natural language commands through human-robot dialog.
In Proceedings of the 2015 International Joint Conference on Artificial Intelligence (IJCAI), July 2015.

151
Fei Fang, Peter Stone, and Milind Tambe.
When security games go green: Designing defender strategies to prevent poaching and illegal fishing.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
Computational Sustainability Outstanding Paper Award.

152
Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone.
Learning inter-task transferability in the absence of target task samples.
In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS). ACM, 2015.

153
Piyush Khandelwal, Samuel Barrett, and Peter Stone.
Leading the way: An efficient multi-robot guidance system.
In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.

154
Jacob Menashe and Peter Stone.
Monte carlo heirarchical model learning.
In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.

155
Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone.
DJ-MC: A reinforcement-learning agent for music playlist recommendation.
In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.

156
Katie Genter, Shun Zhang, and Peter Stone.
Determining placements of influencing agents in a flock.
In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.

157
Samuel Barrett and Peter Stone.
Cooperating with unknown teammates in complex domains: A robot soccer case study of ad hoc teamwork.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 2015.

158
Patrick MacAlpine, Mike Depinet, and Peter Stone.
UT Austin Villa 2014: RoboCup 3D simulation league champion via overlapping layered learning.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.

159
Patrick MacAlpine, Eric Price, and Peter Stone.
SCRAM: Scalable collision-avoiding role assignment with minimal-makespan for formational positioning.
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.

160
Shiqi Zhang and Peter Stone.
Corpp: Commonsense reasoning and probabilistic planning, as applied to dialog with a mobile robot.
In Proceedings of the 29th Conference on Artificial Intelligence (AAAI), January 2015.

161
Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, and Peter Stone.
Communicating with Unknown Teammates.
In Proceedings of the 21st European Conference on Artificial Intelligence (ECAI), August 2014.

162
Patrick MacAlpine, Katie Genter, Samuel Barrett, and Peter Stone.
The RoboCup 2013 drop-in player challenges: Experiments in ad hoc teamwork.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2014.

163
Katie Genter and Peter Stone.
Influencing a flock via ad hoc teamwork.
In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS), September 2014.

164
Daniel Urieli and Peter Stone.
Tactex'13: A champion adaptive power trading agent.
In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI), July 2014.

165
Piyush Khandelwal, Fangkai Yang, Matteo Leonetti, Vladimir Lifschitz, and Peter Stone.
Planning in action language BC while learning action costs for mobile robots.
In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.

166
Noa Agmon, Samuel Barrett, and Peter Stone.
Modeling uncertainty in leading ad hoc teams.
In Proc. of 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2014.

167
W. Bradley Knox, Peter Stone, and Cynthia Breazeal.
Training a robot via human feedback: A case study.
In Proceedings of the International Conference on Social Robotics (ICSR), October 2013.
Best Paper Award.

168
Dustin Carlino, Stephen D. Boyles, and Peter Stone.
Auction-based autonomous intersection management.
In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), September 2013.

169
Daniel Urieli and Peter Stone.
Model-selection for non-parametric function approximation in continuous control problems: A case study in a smart energy system.
In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML), September 2013.

170
Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
Teamwork with limited knowledge of teammates.
In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI), July 2013.

171
Doran Chakraborty and Peter Stone.
Cooperating with a markovian ad hoc teammate.
In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.

172
Todd Hester, Manuel Lopes, and Peter Stone.
Learning exploration strategies in model-based reinforcement learning.
In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.

173
Alon Farchy, Samuel Barrett, Patrick MacAlpine, and Peter Stone.
Humanoid robots learning to walk faster: From the real world to simulation and back.
In Proc. of 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.

174
Katie Genter, Noa Agmon, and Peter Stone.
Ad hoc teamwork for leading a flock.
In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.

175
Daniel Urieli and Peter Stone.
A learning agent for heat-pump thermostat control.
In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.

176
Tsz-Chiu Au, Chien-Liang Fok, Sriram Vishwanath, Christine Julien, and Peter Stone.
Evasion Planning for Autonomous Vehicles at Intersections.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2012.

177
W. Bradley Knox and Peter Stone.
Reinforcement learning from human reward: Discounting in episodic tasks.
In In Proceedings of the 21st IEEE International Symposium on Robot and Human Interactive Communication (Ro-Man), September 2012.
Nominee for Best Paper Award.

178
Todd Hester and Peter Stone.
Intrinsically motivated model learning for a developing curious agent.
In The Eleventh International Conference on Development and Learning (ICDL), November 2012.
Paper of Excellence Award.

179
Dustin Carlino, Mike Depinet, Piyush Khandelwal, and Peter Stone.
Approximately orchestrated routing and transportation analyzer: Large-scale traffic simulation for autonomous vehicles.
In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.

180
Matthew Hausknecht, Piyush Khandelwal, Risto Miikkulainen, and Peter Stone.
Hyperneat-ggp: A hyperneat-based atari general game player.
In Genetic and Evolutionary Computation Conference (GECCO), July 2012.

181
Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, and Peter Stone.
PAC subset selection in stochastic multi-armed bandits.
In John Langford and Joelle Pineau, editors, In proceedings of the 29th International Conference on Machine Learning (ICML), pages 655–662, New York, NY, USA, June-July 2012. Omnipress.

182
Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, and Peter Stone.
Design and optimization of an omnidirectional humanoid walk: A winning approach at the RoboCup 2011 3D simulation competition.
In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI), July 2012.

183
Chien-Liang Fok, Maykel Hanna, Seth Gee, Tsz-Chiu Au, Peter Stone, Christine Julien, and Sriram Vishwanath.
A platform for evaluating autonomous intersection management policies.
In Proceedings of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.

184
W. Bradley Knox and Peter Stone.
Reinforcement learning from simultaneous human and MDP reward.
In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.

185
W. Bradley Knox, Cynthia Breazeal, and Peter Stone.
Learning from feedback on actions past and intended.
In In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports Session (HRI), March 2012.

186
Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Ştiurcă, Victor Vu, and Peter Stone.
UT Austin Villa 2011: A champion agent in the RoboCup 3D soccer simulation competition.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.

187
Noa Agmon and Peter Stone.
Leading ad hoc agents in joint action settings with multiple teammates.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.

188
Noa Agmon, Chien-Liang Fok, Yehuda Emaliah, Peter Stone, Christine Julien, and Sriram Vishwanath.
On coordination in practical multi-robot patrol.
In IEEE International Conference on Robotics and Automation (ICRA), May 2012.

189
Samuel Barrett and Peter Stone.
An analysis framework for ad hoc teamwork tasks.
In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.

190
Tsz-Chiu Au, Michael Quinlan, and Peter Stone.
Setpoint scheduling for autonomous vehicle controllers.
In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.

191
Todd Hester, Michael Quinlan, and Peter Stone.
RTMBA: A real-time model-based reinforcement learning architecture for robot control.
In IEEE International Conference on Robotics and Automation (ICRA), May 2012.

192
Matthew Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, and Travis Waller.
Dynamic Lane Reversal in Autonomous Traffic Management.
In Proceedings of the IEEE Intelligent Transportation systems Society Conference (ITSC), October 2011.

193
Matthew Hausknecht, Tsz-Chiu Au, and Peter Stone.
Autonomous Intersection Management: Multi-Intersection Optimization.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2011.

194
Noa Agmon, Daniel Urieli, and Peter Stone.
Multiagent patrol generalized to complex environmental conditions.
In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI), August 2011.

195
Tsz-Chiu Au, Neda Shahidi, and Peter Stone.
Enforcing Liveness in Autonomous Traffic Management.
In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI), August 2011.

196
Raz Lin, Noa Agmon, Sarit Kraus, Samuel Barrett, and Peter Stone.
Comparing Agents' Success against People in Security Domains.
In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI), August 2011.

197
Doran Chakraborty and Peter Stone.
Structure learning in ergodic factored MDPs without knowledge of the transition function's in-degree.
In Proceedings of the Twenty Eighth International Conference on Machine Learning (ICML), June 2011.

198
Samuel Barrett, Peter Stone, and Sarit Kraus.
Empirical evaluation of ad hoc teamwork in the pursuit domain.
In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.

199
Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone.
On optimizing interdependent skills: A case study in simulated 3d humanoid robot soccer.
In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.

200
David Pardoe and Peter Stone.
A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations.
In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.

201
Michael Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter Stone.
Bringing simulation to life: A mixed reality autonomous intersection.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2010.

202
Tobias Jung and Peter Stone.
Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration.
In The European Conference on Machine Learning (ECML), September 2010.

203
Todd Hester and Peter Stone.
Real time targeted exploration in large domains.
In The Ninth International Conference on Development and Learning (ICDL), August 2010.

204
Doran Chakraborty and Peter Stone.
Convergence, targeted optimality and safety in multiagent learning.
In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML), June 2010.

205
Shivaram Kalyanakrishnan and Peter Stone.
Efficient selection of multiple bandit arms: Theory and practice.
In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML), 2010.

206
David Pardoe and Peter Stone.
Boosting for regression transfer.
In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.

207
Peter Stone, Gal A. Kaminka, Sarit Kraus, and Jeffrey S. Rosenschein.
Ad hoc autonomous agent teams: Collaboration without pre-coordination.
In Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI), July 2010.

208
W. Bradley Knox and Peter Stone.
Combining manual feedback with subsequent MDP reward signals for reinforcement learning.
In Proc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2010.
Best Student Paper Award.

209
David Pardoe, Doran Chakraborty, and Peter Stone.
TacTex09: A champion bidding agent for ad auctions.
In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2010.

210
Peter Stone and Sarit Kraus.
To teach or not to teach? decision making under uncertainty in ad hoc teams.
In The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS). International Foundation for Autonomous Agents and Multiagent Systems, May 2010.

211
Todd Hester, Michael Quinlan, and Peter Stone.
Generalized model learning for reinforcement learning on a humanoid robot.
In IEEE International Conference on Robotics and Automation (ICRA), May 2010.

212
Peter Djeu, Michael Quinlan, and Peter Stone.
Improving particle filter performance using sse instructions.
In Proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), October 2009.

213
W. Bradley Knox and Peter Stone.
Interactively shaping agents via human reinforcement: The TAMER framework.
In The Fifth International Conference on Knowledge Capture, September 2009.

214
Tobias Jung and Peter Stone.
Feature selection for value function approximation using bayesian model selection.
In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), September 2009.

215
Nicholas K. Jong and Peter Stone.
Compositional models for reinforcement learning.
In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), September 2009.

216
Shivaram Kalyanakrishnan and Peter Stone.
An empirical analysis of value function-based and policy search reinforcement learning.
In The Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 749–56, May 2009.

217
Todd Hester and Peter Stone.
Generalized model learning for reinforcement learning in factored domains.
In The Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2009.

218
W. Bradley Knox and Peter Stone.
TAMER: Training an Agent Manually via Evaluative Reinforcement.
In IEEE 7th International Conference on Development and Learning (ICDL), August 2008.

219
Doran Chakraborty and Peter Stone.
Online multiagent learning against memory bounded adversaries.
In Machine Learning and Knowledge Discovery in Databases (ECML), volume 5212 of Lecture Notes in Artificial Intelligence, pages 211–26, September 2008.

220
Matthew E. Taylor, Nicholas K. Jong, and Peter Stone.
Transferring instances for model-based reinforcement learning.
In Machine Learning and Knowledge Discovery in Databases (ECML), volume 5212 of Lecture Notes in Artificial Intelligence, pages 488–505, September 2008.

221
Nicholas K. Jong and Peter Stone.
Hierarchical model-based reinforcement learning: R-MAX + MAXQ.
In Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML), July 2008.

222
Joseph Reisinger, Peter Stone, and Risto Miikkulainen.
Online kernel selection for bayesian reinforcement learning.
In Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML), July 2008.

223
Jonathan Wildstrom, Peter Stone, and Emmett Witchel.
CARVE: A Cognitive Agent for Resource Value Estimation.
In International Conference on Autonomic Computing (ICAC), June 2008.

224
Mohan Sridharan and Peter Stone.
Long-term vs. greedy action planning for color learning on a mobile robot.
In International Conference on Computer Vision Theory and Applications, January 2008.

225
Nicholas K. Jong, Todd Hester, and Peter Stone.
The utility of temporal abstraction in reinforcement learning.
In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2008.

226
Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone.
Autonomous transfer for reinforcement learning.
In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2008.

227
Juhyun Lee and Peter Stone.
Person tracking on a mobile robot with heterogeneous inter-characteristic feedback.
In IEEE International Conference on Robotics and Automation (ICRA), May 2008.

228
Daniel Stronger and Peter Stone.
Maximum likelihood estimation of sensor and action model functions on a mobile robot.
In IEEE International Conference on Robotics and Automation (ICRA), May 2008.

229
Todd Hester and Peter Stone.
Negative information and line observations for monte carlo localization.
In IEEE International Conference on Robotics and Automation (ICRA), May 2008.

230
Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone.
Transfer learning and intelligence: an argument and approach.
In Proceedings of the First Conference on Artificial General Intelligence, March 2008.

231
M. Sridharan and Peter Stone.
Color learning on a mobile robot: Towards full autonomy under changing illumination.
In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2007.

232
Gregory Kuhlmann and Peter Stone.
Graph-based domain mapping for transfer learning in general games.
In Proceedings of The Eighteenth European Conference on Machine Learning (ECML), September 2007.

233
Matthew E. Taylor, Shimon Whiteson, and Peter Stone.
Temporal difference and policy search methods for reinforcement learning: An empirical comparison.
In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI), July 2007.
Nectar Track.

234
Matthew E. Taylor and Peter Stone.
Cross-domain transfer for reinforcement learning.
In Proceedings of the Twenty-Fourth International Conference on Machine Learning (ICML), June 2007.

235
D Stronger and P Stone.
A comparison of two approaches for vision and self-localization on a mobile robot.
In IEEE International Conference on Robotics and Automation (ICRA), April 2007.

236
Matthew E. Taylor, Shimon Whiteson, and Peter Stone.
Transfer via inter-task mappings in policy search reinforcement learning.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2007.

237
Mazda Ahmadi, Matthew E. Taylor, and Peter Stone.
IFSA: Incremental feature-set augmentation for reinforcement learning tasks.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2007.
Nominee for Best Student Paper Award.

238
Shivaram Kalyanakrishnan and Peter Stone.
Batch reinforcement learning in a complex domain.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2007.
Nominee for Best Student Paper Award.

239
Nicholas K. Jong and Peter Stone.
Model-based function approximation for reinforcement learning.
In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2007.

240
Peter Stone.
Learning and multiagent reasoning for autonomous agents.
In The 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 13–30, January 2007.

241
Mohan Sridharan and Peter Stone.
Color learning on a mobile robot: Towards full autonomy under changing illumination.
In The 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 2212–2217, January 2007.

242
Kurt Dresner and Peter Stone.
Sharing the road: Autonomous vehicles meet human drivers.
In The 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 1263–68, January 2007.

243
Bikramjit Banerjee and Peter Stone.
General game learning using knowledge transfer.
In The 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 672–677, January 2007.

244
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin.
Machine learning for on-line hardware reconfiguration.
In The 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 1113–1118, January 2007.

245
Mohan Sridharan and Peter Stone.
Autonomous planned color learning on a mobile robot without labeled data.
In The Ninth International Conference on Control, Automation, Robotics and Vision (ICARCV), December 2006.

246
David Pardoe, Peter Stone, Maytal Saar-Tsechansky, and Kerem Tomak.
Adaptive mechanism design: A metalearning approach.
In The Eighth International Conference on Electronic Commerce (ICEC), pages 92–102, August 2006.

247
Mazda Ahmadi and Peter Stone.
Keeping in touch: Maintaining biconnected structure by homogeneous robots.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages 580–85, July 2006.

248
Shimon Whiteson and Peter Stone.
Sample-efficient evolutionary function approximation for reinforcement learning.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages 518–23, July 2006.

249
David Pardoe and Peter Stone.
TacTex-2005: A champion supply chain management agent.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages 1489–94, July 2006.

250
Gregory Kuhlmann, Kurt Dresner, and Peter Stone.
Automatic heuristic construction in a complete general game player.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages 1457–62, July 2006.

251
Gregory Kuhlmann, William B. Knox, and Peter Stone.
Know thine enemy: A champion RoboCup coach agent.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages 1463–68, July 2006.

252
Yaxin Liu and Peter Stone.
Value-function-based transfer for reinforcement learning using structure mapping.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages 415–20, July 2006.

253
Shimon Whiteson and Peter Stone.
On-line evolutionary computation for reinforcement learning in stochastic domains.
In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 1577–84, July 2006.

254
Harish Subramanian, Subramanian Ramamoorthy, Peter Stone, and Benjamin Kuipers.
Designing safe, profitable automated stock trading agents using evolutionary algorithms.
In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), July 2006.

255
Matthew Taylor, Shimon Whiteson, and Peter Stone.
Comparing evolutionary and temporal difference methods for reinforcement learning.
In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 1321–28, July 2006.
Best Paper Award, GA Track.

256
David Pardoe and Peter Stone.
Predictive planning for supply chain management.
In International Conference on Automated Planning and Scheduling (ICAPS), June 2006.

257
Mazda Ahmadi and Peter Stone.
A multi-robot system for continuous area sweeping tasks.
In IEEE International Conference on Robotics and Automation (ICRA), pages 1724–1729, May 2006.

258
Mohan Sridharan and Peter Stone.
Real-time vision on a mobile robot platform.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), August 2005.

259
Nicholas K. Jong and Peter Stone.
State Abstraction Discovery from Irrelevant State Variables.
In The Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 752–757, August 2005.

260
Mohan Sridharan and Peter Stone.
Autonomous color learning on a mobile robot.
In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), July 2005.

261
Alexander A. Sherstov and Peter Stone.
Improving action selection in MDP's via knowledge transfer.
In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), July 2005.

262
Matthew E. Taylor, Peter Stone, and Yaxin Liu.
Value functions for RL-based behavior transfer: A comparative study.
In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), July 2005.

263
Matthew E. Taylor and Peter Stone.
Behavior transfer for value-function-based reinforcement learning.
In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 53–59, July 2005.

264
Kurt Dresner and Peter Stone.
Multiagent traffic management: An improved intersection control mechanism.
In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2005.

265
Mazda Ahmadi and Peter Stone.
Continuous area sweeping: A task definition and initial approach.
In The 12th International Conference on Advanced Robotics (ICAR), July 2005.

266
Jonathan Wildstrom, Peter Stone, Emmett Witchel, Raymond J. Mooney, and Mike Dahlin.
Towards self-configuring hardware for distributed computer systems.
In The Second International Conference on Autonomic Computing (ICAC), pages 241–249, June 2005.

267
Shimon Whiteson, Peter Stone, Kenneth O. Stanley, Risto Miikkulainen, and Nate Kohl.
Automatic feature selection via neuroevolution.
In The Genetic and Evolutionary Computation Conference (GECCO), June 2005.

268
Mohan Sridharan, Gregory Kuhlmann, and Peter Stone.
Practical vision-based monte carlo localization on a legged robot.
In IEEE International Conference on Robotics and Automation (ICRA), April 2005.

269
Nate Kohl and Peter Stone.
Machine Learning for Fast Quadrupedal Locomotion.
In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pages 611–616, San Jose, CA, July 2004.

270
Kurt Dresner and Peter Stone.
Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism.
In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), New York, NY, July 2004.
Also in The 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV2004), July 2004.

271
Mohan Sridharan and Peter Stone.
Towards On-Board Color Constancy on Mobile Robots.
In the First Canadian Conference on Computer and Robot Vision (CRV), London, Ontario, Canada, May 2004.

272
Nate Kohl and Peter Stone.
Policy Gradient Reinforcement Learning for Fast Quadrapedal Locomotion.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), New Orleans, LA, May 2004.

273
Ronggang Yu and Peter Stone.
Performance analysis of a counter-intuitive automated stock-trading strategy.
In Proceedings of the Fifth International Conference on Electronic Commerce (ICEC), Pittsburgh, PA, October 2003.

274
Satinder Singh, Michael L. Littman, Nicholas K. Jong, David Pardoe, and Peter Stone.
Learning predictive state representations.
In Proceedings of the Twentieth International Conference on Machine Learning (ICML), August 2003.

275
Shimon Whiteson and Peter Stone.
Concurrent layered learning.
In Second International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 193–200, July 2003.

276
Michael P. Wellman, Amy Greenwald, Peter Stone, and Peter R. Wurman.
The 2001 trading agent competition.
In Proceedings of the Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI), July 2002.

277
Robert E. Schapire, Peter Stone, David McAllester, Michael L. Littman, and János A. Csirik.
Modeling auction price uncertainty using boosting-based conditional density estimation.
In Proceedings of the Nineteenth International Conference on Machine Learning (ICML), July 2002.

278
Peter Stone and David McAllester.
An architecture for action selection in robotic soccer.
In Proceedings of the Fifth International Conference on Autonomous Agents (AA), 2001.

279
Charles Lee Isbell Jr., Christian R. Shelton, Michael Kearns, Satinder Singh, and Peter Stone.
A social reinforcement learning agent.
In Proceedings of the Fifth International Conference on Autonomous Agents (AA), 2001.
Best Paper Award.

280
Peter Stone, Patrick Riley, and Manuela Veloso.
Defining and using ideal teammate and opponent agent models.
In Proceedings of the Twelfth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2000.

281
Peter Stone.
TPOT-RL applied to network routing.
In Proceedings of the Seventeenth International Conference on Machine Learning (ICML), pages 935–942, 2000.

282
Manuela Veloso, Michael Bowling, Sorin Achim, Kwun Han, and Peter Stone.
CMUnited-98: A team of robotic soccer agents.
In Proceedings of the Eleventh Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 1999.

283
Manuela Veloso, Peter Stone, and Michael Bowling.
Anticipation as a key for collaboration in a team of agents: A case study in robotic soccer.
In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, volume 3839, pages 134–143, Boston, September 1999.

284
Manuela Veloso and Peter Stone.
Individual and collaborative behaviors in a team of homogeneous robotic soccer agents.
In Proceedings of the Third International Conference on Multi-Agent Systems (ICMAS), pages 309–316, 1998.

285
Hiroaki Kitano, Milind Tambe, Peter Stone, Manuela Veloso, Silvia Coradeschi, Eiichi Osawa, Hitoshi Matsubara, Itsuki Noda, and Minoru Asada.
The RoboCup synthetic agent challenge 97.
In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 24–29, San Francisco, CA, 1997. Morgan Kaufmann.

286
Gregg Rabideau, Steve Chien, Peter Stone, Jason Willis, Curt Eggemeyer, and Tobias Mann.
Interactive, repair-based planning and scheduling for shuttle payload operations.
In Proceedings of the 1997 IEEE Aerospace Conference, pages 325–341, Aspen, CO, February 1997.

287
Manuela Veloso, Peter Stone, and Sorin Achim.
A layered approach for an autonomous robotic soccer system.
In Proceedings of the First International Conference on Autonomous Agents (AA), pages 530–531, Marina del Rey, CA, February 1997.

288
Peter Stone and Manuela Veloso.
Beating a defender in robotic soccer: Memory-based learning of a continuous function.
In David S. Touretzky, Michael C. Mozer, and Michael E. Hasselmo, editors, Advances in Neural Information Processing Systems 8 (NIPS), pages 896–902, Cambridge, MA, 1996. MIT Press.

289
Peter Stone, Manuela Veloso, and Jim Blythe.
The need for different domain-independent heuristics.
In Proceedings of the Second International Conference on AI Planning Systems (AIPS), pages 164–169, June 1994.



Refereed Workshop and Symposium Papers

1
Juan Huerta, Bo Liu, and Peter Stone.
VaryNote: a method to automatically vary the number of notes in symbolic music.
In The 16th International Symposium on Computer Music Multidisciplinary Research, (CMMR), Lecture Notes in Computer Science. Springer, November 2023.

2
Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu Xiao, Garrett Warnell, Joydeep Biswas, and Peter Stone.
Visually adaptive geometric navigation.
In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2023.

3
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.
"what's that robot doing here?": Factors influencing perceptions of incidental encounters with autonomous quadruped robots.
In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS), pages 1–15, July 2023.

4
Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri, and Peter Stone.
Program embeddings for rapid mechanism evaluation.
In ICRA workshop on Multi-Robot Learning, May 2023.

5
Swathi Mannem, William Macke, Peter Stone and Reuth Mirsky.
Exploring the cost of interruptions in human-robot teaming.
In AAMAS workshop on Rebellion and disobedience in AI (RaD-AI23), May 2023.
Best Paper Award.

6
Anthony Francis, Claudia Perez-D'Arpino, Chengshu Li, Fei Xia, Alexandre Alahi, Rachid Alami1, Aniket Bera, Abhijat Biswas, Joydeep Biswas, Rohan Chandra, Hao-Tien Lewis Chiang, Michael Everett, Sehoon Ha, Justin Hart, Jonathan P. How, Haresh Karnan, Tsang-Wei Edward Lee, Luis J. Manso, Reuth Mirksy, Soren Pirk, Phani Teja Singamaneni, Peter Stone, Ada V. Taylor, Peter Trautman, Nathan Tsoi, Marynel Vazquez, Xuesu Xiao, Peng Xu, Naoki Yokoyama, Alexander Toshev, and Roberto Martin-Martin
Benchmarking social robot navigation across academia and industry
In AAAI Spring Symposium on "HRI in Academia and Industry: Bridging the Gap, March 2023.
arXiv e-Prints 2306.16740.
Nominee for Best Paper Award.

7
Eddy Hudson, Ishan Durugkar, Garrett Warnell, and Peter Stone.
ABC: Adversarial Behavioral Cloning for offline mode-seeking imitation learning
In NeurIPS 2022 Workshop on Deep RL, December 2022.
arXiv e-Prints 2211.04005.

8
Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, and Peter Stone.
Dynabarn: Benchmarking metric ground navigation in dynamic environments.
In Proceedings of the 2022 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2022.

9
Yair Hanina, Reuth Mirsky, William Macke, and Peter Stone.
Quantifying human rationality in ad-hoc teamwork.
In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.

10
Yulin Zhang, William Macke, Jiaxun Cui, Daniel Urieli, and Peter Stone.
Learning a robust multiagent driving policy for traffic congestion reduction.
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2022.

11
Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yulin Zhan, Yuqian Jiang, Bo Liu, and Peter Stone.
Model-based meta automatic curriculum learning.
In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.

12
Reuth Mirsky, Shahaf S. Shperberg, Yulin Zhang, Zifan Xu, Yuqian Jiang, Jiaxun Cui, and Peter Stone.
Task factorization in curriculum learning.
In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.

13
Sai Kiran Narayanaswami, Swarat Chauduri, Moshe Vardi, and Peter Stone.
Automating mechanism design with program synthesis.
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2022.

14
Caroline Wang, Ishan Durugkar, Elad Liebman, and Peter Stone.
Decentralized multi-agent reinforcement learning via distribution matching.
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2022.

15
Parth Chonkar, Geethika Hemkumar, Huihai Wang, Daksh Dua, Shikhar Gupta, Yao-Cheng Chan, Justin Hart, Elliott Hauser, Reuth Mirsky, Joydeep Biswas, Junfeng Jiao, and Peter Stone.
Look to my Lead: How does a leash affect perceptions of a quadruped robot?
In ICRA workshop on Social Navigation, May 2022.

16
Hager Radi, Josiah P. Hanna, Peter Stone, and Matthew E. Taylor.
Leveraging information about background music in human-robot interaction.
In NeurIPS Workshop on Deployable Decision Making in Embodied Systems (DDM), Decmeber 2021.

17
Elad Liebman and Peter Stone. Leveraging information about background music in human-robot interaction.
In NeurIPS Workshop on Human and Machine Decisions, Decmeber 2021.

18
Reuth Mirsky and Peter Stone.
Intelligent disobedience and AI rebel agents in assistive robotics.
In ICSR workshop on Adaptive Social Interaction and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.

19
Zifan Xu, Xuesu Xiao, Garrett Warnell, Anirudh Nair, and Peter Stone.
Machine learning methods for local motion planning: A study of end-to-end vs. parameter learning.
In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), October 2021.

20
Justin Hart, Reuth Mirsky, Xuesu Xiao, and Peter Stone.
Incorporating gaze into social navigation.
In RSS Workshop on Social Robot Navigation, July 2021.

21
Yuchen Cui, Akanksha Saran, Bo Liu, Scott Niekum, Stephen Giguere, and Peter Stone.
Aux-AIRL: End-to-End Self-Supervised Reward Learning for Extrapolating beyond Suboptimal Demonstrations.
In ICML workshop on Self-Supervised Learning for Reasoning and Perception, July 2021.

22
Bharath Masetty, Reuth Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter Stone.
Is the cerebellum a model-based reinforcement learning agent?
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2021.

23
Jennifer Suriadinata, William Macke, Reuth Mirsky, and Peter Stone.
Reasoning about human behavior in ad hoc teamwork.
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2021.

24
Eddy Hudson, Garrett Warnell, and Peter Stone.
Rail: A modular framework for reinforcement-learning-based adversarial imitation learning.
In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2021.

25
Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, and W. Bradley Knox.
Reaction Modeling for Deriving General Task Information from Implicit Human Feedback.
In HRI workshop on Exploring Applications for Autonomous Nonverbal Human-Robot Interaction, March 2021.

26
Haresh Karnan, Garrett Warnell, Xuesu Xiao, and Peter Stone.
VOILA : Visual-Observation-only Imitation Learning for Autonomous navigation.
In AAAI Spring Symposium on Machine Learning for Mobile Robot Navigation in the Wild, March 2021.

27
Minkyu Kim, Miguel Arduengo, Nick Walker, Yuqian Jiang, Hart W. Justin, Peter Stone, and Luis Sentis.
Active Target Search for Autonomous Person Following.
In AAAI Spring Symposium on Machine Learning for Mobile Robot Navigation in the Wild, March 2021.

28
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone.
Safe Learning from Hallucination for Navigation in the Wild.
In AAAI Spring Symposium on Machine Learning for Mobile Robot Navigation in the Wild, March 2021.

29
William Macke, Reuth Mirsky, and Peter Stone.
Expected Divergence Point of Plans in Ad Hoc Teamwork.
In Cooperative AI Workshop at NeurIPS 2020 (CoopAI), December 2020.

30
Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone.
On sampling error in batch action-value prediction algorithms.
In In the Offline Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), December 2020., December 2020.

31
Daniel Perille, Abigail Truong, Xuesu Xiao, and Peter Stone.
Benchmarking metric ground navigation.
In special session on Performance Evaluation & Benchmarking for Disaster Robotics at International Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2020.

32
Xuesu Xiao, Bo Liu, and Peter Stone.
Motion planners learned from geometric hallucination.
In IROS workshop on bringing geometric methods to robot learning, optimization and control, October 2020.

33
Keya Ghonasgi, Reuth Mirsky, Bharath Masetty, Sanmit Narvekar, Adrian Haith, Peter Stone, and Ashish Deshpande.
Leveraging reinforcement learning for human motor skill acquisition.
In 13th International Workshop on Human Friendly Robotics (HFR), October 2020.

34
William Macke, Reuth Mirsky and Peter Stone.
Query content in sequential one-shot multi-agent limited inquiries when communicating in ad hoc teamwork.
In Workshop on Distributed and Multi-Agent Planning (DMAP), October 2020.

35
Sanmit Narvekar and Peter Stone.
Generalizing curricula for reinforcement learning.
In ICML Workshop on Lifelong Learning, July 2020.

36
Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor.
Work-in-progress: Corrected Self Imitation learning via Demonstrations.
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2020.

37
Harel Yedidsion, Alkoby Shani, and Peter Stone.
Sequential online chore division for autonomous vehicle convoy formation.
In AAMAS workshop on Games, Agents and Incentives Workshop (GAIW), May 2020.

38
Rishi Shah, Yuqian Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta, Rachel Schlossman, Marika Murphy, Justin Hart, Luis Sentis and Peter Stone.
Solving Service Robot Tasks: UT Austin VillaHome 2019 Team Report.
In Proceedings of the AAAI Fall Symposium on Artificial Intelligence for Human-Robot Interaction, November 2019.

39
Nick Walker, Yuqian Jiang, Maya Cakmak and Peter Stone.
Desiderata for Planning Systems in General Purpose Service Robots.
In ICAPS workshop on Planning for Robotics (PlanRob), July 2019.

40
Faraz Torabi, Garrett Warnell, and Peter Stone.
Generative adversarial imitation from observation.
In ICML Workshop on Imitation, Intent, and Interaction (I3) Workshop, June 2019.

41
Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone.
Sample-efficient adversarial imitation learning from observation.
In ICML Workshop on Imitation, Intent, and Interaction (I3) Workshop, June 2019.

42
Felipe Leno Da Silva and Peter Stone.
Distributional Reinforcement Learning Applied to Robot Soccer Simulation.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), May 2019.

43
Shih-Yun Lo, Shani Alkoby and Peter Stone.
Robust Motion Planning and Safety Benchmarking in Human Workspaces.
In AAAI workshop on Safe AI, January 2019.

44
Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, and Peter Stone.
LAAIR: A layered architecture for autonomous interactive robots.
In Proceedings of the AAAI Fall Symposium on Reasoning and Learning in Real-World Systems for Long-Term Autonomy, October 2018.

45
Prabhat Nagarajan, Garrett Warnell, and Peter Stone.
Deterministic implementations for reproducibility in deep reinforcement learning.
In 2nd ICML Workshop on Reproducibility in Machine Learning, July 2018.

46
Jake Menashe and Peter Stone.
State abstraction synthesis for discrete models of continuous domains.
In Proceedings of the AAAI Spring Symposium on Data Efficient Reinforcement Learning (DERL), March 2018.

47
Ishan Durugkar and Peter Stone
TD learning with constrained gradients.
In NIPS Deep Reinforcement Learning Symposium, December 2017.

48
Josiah Hanna and Peter Stone.
Towards a data efficient off-policy policy gradient.
In AAAI Spring Symposium on Data Efficient Reinforcement Learning, March 2018.

49
Santiago Gonzalez, Vijay Chidambaram, Jivko Sinapov, and Peter Stone.
CC-Log: Drastically reducing storage requirements for robots using classification and compression.
In The 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage), July 2017.

50
Shih-Yun Lo, Benito Fernandez, and Peter Stone.
Iterative Human-Aware Mobile Robot Navigation.
In RSS Workshop on Human-Centered Robotics: Interaction, Physiological Integration, and Autonomy, July 2017.

51
Shiqi Zhang and Peter Stone.
Integrated Commonsense Reasoning and Probabilistic Planning.
In ICAPS workshop on Planning for Robotics, June 2017.

52
Shiqi Zhang, Jivko Sinapov, Suhua Wei, and Peter Stone.
Robot behavioral exploration and multimodal perception using POMDPs.
In Proceedings of the AAAI Spring Symposium on Interactive Multi-Sensory Perception for Embodied Agents, March 2017.

53
Matthew Hausknecht and Peter Stone.
Grounded semantic networks for learning shared communication protocols.
In NIPS workshop on Deep Reinforcement Learning, December 2016.

54
Patrick MacAlpine, Elad Liebman, and Peter Stone.
Adaptation of surrogate tasks for bipedal walk optimization.
In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.

55
Matthew Hausknecht and Peter Stone.
On-policy vs. off-policy updates for deep reinforcement learning.
In IJCAI 2016 Workshop on Deep Reinforcement Learning, July 2016.

56
Ginevra Gaudioso, Matteo Leonetti, and Peter Stone.
State aggregation through reasoning in answer set programming.
In Proceedings of the IJCAI Workshop on Autonomous Mobile Service Robots (WSR), July 2016.

57
Josiah P. Hanna, Michael Albert, Donna Chen, and Peter Stone.
Minimum cost matching for autonomous carsharing.
In Proceedings of the 9th IFAC Symposium on Intelligent Autonomous Vehicles (IAV), June 2016.

58
Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone.
Half field offense: An environment for multiagent learning and ad hoc teamwork.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), May 2016.

59
Matthew Hausknecht, Yilun Chen, and Peter Stone.
Deep imitation learning for parameterized action spaces.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), May 2016.

60
Jonathan Grizou, Samuel Barrett, Manuel Lopes, and Peter Stone.
Collaboration in ad hoc teamwork: ambiguous tasks, roles, and communication.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), May 2016.

61
Matthew Hausknecht and Peter Stone.
Deep recurrent Q-learning for partially observable MDPs.
In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (SDMIA), November 2015.

62
Matthew Hausknecht and Peter Stone.
The impact of determinism on learning atari 2600 games.
In AAAI Workshop on Learning for General Competency in Video Games, January 2015.

63
Piyush Khandelwal and Peter Stone.
Multi-robot human guidance using topological graphs.
In AAAI Spring 2014 Symposium on Qualitative Representations for Robots, March 2014.

64
Fangkai Yang, Piyush Khandelwal, Matteo Leonetti, and Peter Stone.
Planning in answer set programming while learning action costs for mobile robots.
In AAAI Spring 2014 Symposium on Knowledge Representation and Reasoning in Robotics, March 2014.

65
Jacob Menashe, Katie Genter, Samuel Barrett, and Peter Stone.
UT Austin Villa 2013: Advances in vision, kinematics, and strategy.
In The Eighth Workshop on Humanoid Soccer Robots at Humanoids 2013, October 2013.

66
Katie Genter, Noa Agmon, and Peter Stone.
Improving efficiency of leading a flock in ad hoc teamwork settings.
In AAMAS Workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2013.

67
Patrick MacAlpine, Elad Liebman, and Peter Stone.
Simultaneous learning and reshaping of an approximated optimization task.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), May 2013.

68
Doran Chakraborty, Noa Agmon, and Peter Stone.
Targeted opponent modeling of memory-bounded agents.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), May 2013.

69
Patrick MacAlpine and Peter Stone.
Using dynamic rewards to learn a fully holonomic bipedal walk.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), June 2012.

70
Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
Learning teammate models for ad hoc teamwork.
In AAMAS Workshop on Adaptive and Learning Agents (ALA), June 2012.

71
W. Bradley Knox, Matthew Taylor, and Peter Stone.
Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report
In IJCAI workshop on Agents Learning Interactively from Human Teachers (ALIHT), July 2011.

72
W. Bradley Knox and Peter Stone.
Augmenting Reinforcement Learning with Human Feedback.
In ICML Workshop on Imitation Learning, July 2011.

73
Paul Scerri, Balajee Kannan, Pras Velagapudi, Kate Macarthur, Peter Stone, Matthew E. Taylor, John Dolan, Alessandro Farinelli, Archie Chapman, Bernadine Dias, and George Kantor.
Flood disaster mitigation: A real-world challenge problem for multi-agent unmanned surface vehicles.
In Proceedings of the AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2011.

74
Samuel Barrett and Peter Stone.
Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
In Proceedings of the AAMAS workshop on Adaptive Learning Agents (ALA), May 2011.

75
Shivaram Kalyanakrishnan and Peter Stone.
On learning with imperfect representations.
In Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, April 2011.

76
Shimon Whiteson, Brian Tanner, Matthew E. Taylor, and Peter Stone.
Protecting against evaluation overfitting in empirical reinforcement learning.
In IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), April 2011.

77
W. Bradley Knox and Peter Stone.
Reinforcement learning with human feedback in mountain car.
In AAAI Spring 2011 Symposium on Bridging the Gaps in Human-Agent Collaboration, March 2011.

78
Samuel Barrett, Katie Genter, Todd Hester, Michael Quinlan, and Peter Stone.
Controlled kicking under uncertainty.
In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.

79
Piyush Khandelwal, Matthew Hausknecht, Juhyun Lee, Aibo Tian, and Peter Stone.
Vision calibration and processing on a humanoid soccer robot.
In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.

80
Adam Setapen, Michael Quinlan, and Peter Stone.
MARIOnET: motion acquisition for robots through iterative online evaluative training.
In AAMAS 2010 Workshop on Agents Learning Interactively from Human Teachers (ALIHT), May 2010.

81
Samuel Barret, Matthew E. Taylor, and Peter Stone.
Transfer learning for reinforcement learning on a physical robot
In AAMAS 2010 Workshop on Adaptive and Learning Agents (ALA), May 2010.

82
Tobias Jung, Mazda Ahmadi, and Peter Stone.
Connectivity-based localization in robot networks.
In International Workshop on Robotic Wireless Sensor Networks (WSN), June 2009.

83
Todd Hester and Peter Stone.
An empirical comparison of abstraction in models of markov decision processes.
In Proceedings of the ICML/UAI/COLT Workshop on Abstraction in Reinforcement Learning, June 2009.

84
Ian Fasel, Michael Quinlan, and Peter Stone.
A task specification language for bootstrap learning.
In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.

85
W. Bradley Knox, Ian Fasel, and Peter Stone.
Design principles for creating human-shapable agents.
In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.

86
Mohan Sridharan and Peter Stone.
Comparing two action planning approaches for color learning on a mobile robot.
In VISAPP Workshop on Robotic Perception, January 2008.

87
Kurt Dresner and Peter Stone.
Learning policy selection for autonomous intersection management.
In AAMAS workshop on Adaptive and Learning Agents (ALA), May 2007.

88
Matthew E. Taylor and Peter Stone.
Representation transfer for reinforcement learning.
In AAAI 2007 Fall Symposium on Computational Approaches to Representation Change during Learning and Development, November 2007.

89
Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone.
Accelerating search with transferred heuristics.
In ICAPS workshop on AI Planning and Learning, September 2007.

90
Nicholas K. Jong and Peter Stone.
Model-based exploration in continuous state spaces.
In The Seventh Symposium on Abstraction, Reformulation, and Approximation, July 2007.

91
Nicholas Jong and Peter Stone.
Kernel-based models for reinforcement learning in continuous state spaces.
In ICML workshop on Kernel Machines and Reinforcement Learning, June 2006.

92
Matthew E. Taylor, Shimon Whiteson, and Peter Stone.
Transfer learning for policy search methods.
In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.

93
Bikramjit Banerjee, Gregory Kuhlmann, and Peter Stone.
Value function transfer for general game playing.
In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.

94
Daniel Stronger and Peter Stone.
Expectation-based vision for precise self-localization on a mobile robot.
In AAAI workshop on Cognitive Robotics, July 2006.

95
Mazda Ahmadi and Peter Stone.
Instance-based action models for fast action planning.
In AAAI workshop on Cognitive Robotics, July 2006.

96
Peter Stone, David Pardoe, and Mark VanMiddlesworth.
TacTex-05: An adaptive agent for TAC SCM.
In AAMAS 2006 Joint workshop on Trading Agent Design and Analysis & Agent Mediated Electronic Commerce VIII, May 2006.

97
Kurt Dresner and Peter Stone.
Human-usable and emergency vehicle-aware control policies for autonomous intersection management.
In AAMAS 2006 Workshop on Agents in Traffic and Transportation, May 2006.

98
Mazda Ahmadi and Peter Stone.
Keeping in touch: A distributed check for biconnected structure by homogeneous robots.
In The 8th International Symposium on Distributed Autonomous Robotic Systems, July 2006.

99
Subramanian Ramamoorthy, Harish Subramanian, Peter Stone, and Benjamin Kuipers.
A qualitative multiple-model approach to the design of autonomous financial trading agents.
In NIPS 2005 workshop on Machine Learning in Finance, December 2005.

100
Nicholas K. Jong and Peter Stone.
Bayesian models of nonstationary markov decision problems.
In IJCAI 2005 workshop on Planning and Learning in A Priori Unknown or Dynamic Domains, August 2005.

101
Nicholas K. Jong and Peter Stone.
Towards learning to ignore irrelevant state variables.
In The AAAI-2004 Workshop on Learning and Planning in Markov Processes – Advances and Challenges, July 2004.

102
Gregory Kuhlmann, Peter Stone, Raymond Mooney, and Jude Shavlik.
Guiding a reinforcement learner with natural language advice: Initial results in RoboCup soccer.
In The AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, July 2004.

103
János A. Csirik, Michael L. Littman, Satinder Singh, and Peter Stone.
FAucS: An FCC spectrum auction simulator for autonomous bidding agents.
In Ludger Fiege, Gero Mühl, and Uwe Wilhelm, editors, Electronic Commerce: Proceedings of the Second International Workshop. Springer Verlag, Heidelberg, 2001.

104
Michael L. Littman and Peter Stone.
Implicit Negotiation in Repeated Games.
In Proceedings of The Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL), 2001.

105
M. Asada, A. Birk, E. Pagello, M. Fujita, I. Noda, S. Tadokoro D. Duhaut, P. Stone, M. Veloso, T. Balch, H. Kitano, and B. Thomas.
Progress in RoboCup soccer research in 2000.
In Proceedings of the 2000 International Symposium on Experimental Robotics, Honolulu, 2000.

106
Patrick Riley, Peter Stone, and Manuela Veloso.
Layered disclosure: Revealing agents' internals.
In The Seventh International Workshop on Agent Theories, Architectures, and Languages (ATAL), 2000.

107
Peter Stone.
Multiagent learning for autonomous spacecraft constellations.
In Proceedings of the NASA Workshop on Planning and Scheduling for Space, 1997.

108
Sorin Achim, Peter Stone, and Manuela Veloso.
Building a dedicated robotic soccer system.
In Proceedings of the IROS-96 Workshop on RoboCup, pages 41–48, Osaka, Japan, November 1996.

109
Mike Bowling, Peter Stone, and Manuela Veloso.
Predictive memory for an inaccessible environment.
In Proceedings of the IROS-96 Workshop on RoboCup, pages 28–34, Osaka, Japan, November 1996.

110
Peter Stone and Manuela Veloso.
Using machine learning in the soccer server.
In Proceedings of the IROS-96 Workshop on RoboCup, pages 19–27, Osaka, Japan, November 1996.

111
Peter Stone, Manuela Veloso, and Sorin Achim.
Collaboration and learning in robotic soccer.
In Proceedings of the Micro-Robot World Cup Soccer Tournament, pages 26–37, Taejon, Korea, November 1996. IEEE Robotics and Automation Society.

112
Peter Stone and Manuela Veloso.
Using testing to iteratively improve training.
In Working Notes of the AAAI 1995 Fall Symposium on Active Learning, pages 110–111, Boston, MA, November 1995.

113
Peter Stone and Manuela Veloso.
Learning to solve complex planning problems finding useful auxiliary problems.
In Technical Report of the AAAI 1994 Fall Symposium on Planning and Learning: On to Real Applications, pages 137–141, New Orleans, LA, November 1994.



Magazine Articles

1
Xuesu Xiao, Zifan Xu, Aniket Datar, Garrett Warnell, Peter Stone, Joshua Julian Damanik, Jaewon Jung, Chala Adane Deresa, Than Duc Huy, Chen Jinyu, Chen Yichen, Joshua Adrian Cahyono, Jingda Wu, Longfei Mo, Mingyang Lv, Bowen Lan, Qingyang Meng, Weizhi Tao, and Li Cheng.
Autonomous ground navigation in highly constrained spaces: Lessons learned from the third BARN challenge at ICRA 2024 [competitions].
IEEE Robotics & Automation Magazine, 2024.

2
Eric Horvitz, Vincent Conitzer, Sheila McIlraith, and Peter Stone.
Now, later, and lasting: 10 priorities for AI research, policy, and practice.
Communications of the ACM, 67(6):39–40, May 2024.

3
Peter Stone.
Will robots triumph over world cup winners by 2050?
IEEE Spectrum, 60(7):40–9, July 2023.

4
Xuesu Xiao, Zifan Xu, Garrett Warnell, Peter Stone, Ferran Bebelli Guinjoan, Romulo T. Rodrigues, Herman Bryunickx, Hanjaya Mandala, Guilherme Christmann, Jose Luis Blanco-Claraco, and Shravan Somashekara Rai.
Autonomous ground navigation in highly constrained spaces: lessons learned from the 2nd BARN challenge at ICRA 2023.
IEEE Robotics & Automation Magazine, 30(4):91–97, Dec. 2023.

5
Xuesu Xiao, Zifan Xu, Zizhao Wang, Yunlong Song, Garrett Warnell, Peter Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, and Philip Dames.
Autonomous ground navigation in highly constrained spaces: Lessons learned from the barn challenge at icra 2022.
IEEE Robotics & Automation Magazine, 29(4):148–56, Dec. 2022.

6
Peter R. Wurman, Peter Stone, and Michael Sprannger.
Challenges and opportunities of applying reinforcement learning to autonomous racing.
IEEE Intelligent Systems, 37(3):20–3, May-June 2022.

7
Peter Stone, Luca Iocchi, Flavio Tonidandel, and Changjiu Zhou.
RoboCup 2021 worldwide: a successful robotics competition during a pandemic.
IEEE Robotics & Automation Magazine, 28(4):114–19, December 2021.

8
Barbara J. Grosz and Peter Stone.
A century long commitment to assessing artificial intelligence and its impact on society.
Communications of the ACM, 61(12), December 2018.

9
Tsz-Chiu Au, Bikramjit Banerjee, Prithviraj Dasgupta, Peter Stone.
Guest Editors' Introduction: Multirobot Systems.
In IEEE Intelligent Systems, pages 3–5, November/December 2017.

10
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.
Who Speaks for AI?
in AI Matters, 2(2), December 2015.

11
Daniele Nardi, Itsuki Noda, Fernando Ribeiro, Peter Stone, Oskar von Stryk, and Manuela Veloso.
RoboCup soccer leagues.
AI Magazine, 35(3):77–85, 2014.

12
David Pardoe and Peter Stone.
Designing Adaptive Trading Agents.
ACM SIGecom Exchanges, 10(2), June 2011.

13
Matthew E. Taylor and Peter Stone.
An Introduction to Inter-task Transfer for Reinforcement Learning.
AI Magazine, 32(1):15–20, March 2011.

14
David Pardoe and Peter Stone.
Developing Adaptive Auction Mechanisms.
ACM SIGecom Exchanges, 5(3):1–10, April 2005.

15
David Pardoe and Peter Stone.
TacTex-03: A Supply Chain Management Agent.
ACM SIGecom Exchanges, 4(3):19–28, Winter 2004.

16
Amy Greenwald, Nicholas R. Jennings, and Peter Stone.
Guest Editors' Introduction: Agents and Markets.
IEEE Intelligent Systems, 18(6):12–14, November/December 2003.

17
Manuela Veloso, Tucker Balch, Peter Stone, Hiroaki Kitano, Fuminori Yamasaki, Ken Endo, Minoru Asada, M. Jamzad, B. S. Sadjad, V. S. Mirrokni, M. Kazemi, H. Chitsaz, A. Heydarnoori, M. T. Hajiaghai, and E. Chiniforooshan.
RoboCup-2001: The fifth robotic soccer world championships.
AI Magazine, 23(1):55–68, 2002.

18
Peter Stone (editor), 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.
RoboCup-2000: The fourth robotic soccer world championships.
AI Magazine, 22(1), 2001.

19
Amy Greenwald and Peter Stone.
Autonomous bidding agents in the trading agent competition.
IEEE Internet Computing, 5(2), 2001.

20
Silvia Coradeschi, Lars Karlsson, Peter Stone, Tucker Balch, Gerhard Kraetzschmar, and Minoru Asada.
Overview of RoboCup-99.
AI Magazine, 21(3), 2000.

21
Manuela Veloso, Peter Stone, Kwun Han, and Sorin Achim.
CMUnited: A team of robotic soccer agents collaborating in an adversarial environment.
Crossroads, 4.3, February 1998.



Multimedia

1
Manuela Veloso and Peter Stone.
Video: Robocup robot soccer history 1997 – 2011, October 2012.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2012.
Available from https://www.youtube.com/watch?v=WLOv2AFAZhc
Finalist for Best Video Award.

2
W. Bradley Knox, Juhyun Lee, and Peter Stone.
Person recognition on a segway robot: A video of UT Austin Villa Robocup@Home 2007 finals demonstration.
In IEEE International Conference on Robotics and Automation, May 2008.
Available from www.cs.utexas.edu/~AustinVilla/?p=athome



Unrefereed Publications

1
Elad Liebman and Peter Stone.
Utilizing mood-inducing background music in human-robot interaction.
arXiv e-Prints 2308.14269, September 2023.

2
Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone.
LLM+P: empowering large language models with optimal planning proficiency.
arXiv e-Prints 2304.11477, April 2023.

3
Justin Hart, Harel Yedidsion, Yuqian Jiang, Nick Walker, Rishi Shah, Jesse Thomason, Aishwarya Padmakumar, Rolando Fernandez, Jivko Sinapov, Raymond Mooney, and Peter Stone.
Interaction and autonomy in RoboCupHome and Building-Wide Intelligence.
In Proceedings of the AAAI Fall Symposium on Interactive learning in Artificial Intelligence for Human-Robot Interaction (AI-HRI), October 2018.

4
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.
Bringing smart transport to texans: Ensuring the benefits of a connected and autonomous transport system in texas — final report.
Technical Report 0-6838-3, The University of Texas at Austin Center for Transportation Research, July 2018.

5
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.
An assessment of autonomous vehicles: traffic impacts and infrastructure needs — final report.
Technical Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, March 2017.

6
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.
Bringing smart transport to texans: Ensuring the benefits of a connected and autonomous transport system in texas — final report.
Technical Report 0-6838-2, The University of Texas at Austin Center for Transportation Research, November 2016.

7
Decebal Constantin Mocanu, Maria Torres Vega, Eric Eaton, Peter Stone, and Antonio Liotta.
Online contrastive divergence with generative replay: Experience replay without storing data.
arXiv e-Prints 1610.05555, October 2016.

8
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.
Artificial Intelligence and life in 2030.
One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.

9
Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Ştiurcă, Victor Vu, and Peter Stone.
UT Austin Villa 2011 3D Simulation Team report.
Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory, December 2011.

10
Samuel Barrett, Katie Genter, Matthew Hausknecht, Todd Hester, Piyush Khandelwal, Juhyun Lee, Michael Quinlan, Aibo Tian, Peter Stone, and Mohan Sridharan.
Austin Villa 2010 standard platform team report.
Technical Report UT-AI-TR-11-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, January 2011.

11
Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan.
TT-UT Austin Villa 2009: Naos across Texas.
Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory, December 2009.

12
Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone.
The UT Austin Villa 3D Simulation Soccer Team 2008.
Technical Report AI09-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, February 2009.

13
Todd Hester, Michael Quinlan, and Peter Stone.
UT Austin Villa 2008: Standing on Two Legs.
Technical Report UT-AI-TR-08-8, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, November 2008.

14
Shivaram Kalyanakrishnan and Peter Stone.
UT Austin Villa 3D simulation soccer team 2008.
In RoboCup Symposium CD Proceedings, 2008.

15
Peter Stone Todd Hester, Michael Quinlan.
UT Austin Villa 2008 team description paper for the standard platform league.
In RoboCup Symposium CD Proceedings, 2008.

16
Peter Stone and Neda Shahidi.
The UT Austin Villa 2008 mixed reality team.
In RoboCup Symposium CD Proceedings, 2008.

17
Peter Stone, Patrick Beeson, Tekin Mericli, and Ryan Madigan.
DARPA urban challenge technical report: Austin Robot Technology, June 2007.

18
Shivaram Kalyanakrishnan and Peter Stone.
The UT Austin Villa 3D Simulation Soccer Team 2007.
Technical Report AI-07-348, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, September 2007.

19
Shimon Whiteson, Matthew E. Taylor, and Peter Stone.
Adaptive tile coding for value function approximation.
Technical Report AI-TR-07-339, University of Texas at Austin, 2007.

20
Peter Stone, William B. Knox, Juhyun Lee, Youngin Shin, and Mohan Sridharan.
The UT Austin Villa 2007 team description paper.
In RoboCup Symposium CD Proceedings, 2007.

21
Peter Stone, Todd Hester, Tekin Meriçli, Neda Shahidi, and Mohan Sridharan.
The UT Austin Villa 2007 four-legged team description paper.
In RoboCup Symposium CD Proceedings, 2007.

22
Peter Stone, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Tekin Mericli, Mohan Sridharan, and Shao en Yu.
The UT Austin Villa 2006 RoboCup four-legged team.
Technical Report UT-AI-TR-06-337, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, December 2006.

23
Daniel Stronger and Peter Stone.
Polynomial regression with automated degree: A function approximator for autonomous agents.
Technical Report UT-AI-TR-06-329, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, April 2006.

24
Peter Stone, Kurt Dresner, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger.
The UT Austin Villa 2005 RoboCup four-legged team.
Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, November 2005.

25
Kurt Dresner and Peter Stone.
Multiagent traffic management: Driver agent improvements and a protocol for intersection control.
Technical Report UT-AI-TR-04-315, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, May 2005.

26
Peter Stone, Kurt Dresner, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger.
The UT Austin Villa 2004 RoboCup four-legged team: Coming of age.
Technical Report UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, October 2004.

27
Nicholas K. Jong and Peter Stone.
Towards employing PSRs in a continuous domain.
Technical Report UT-AI-TR-04-309, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, February 2004.

28
Peter Stone, Kurt Dresner, Selim T. Erdogan, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Ellie Lin, Mohan Sridharan, Daniel Stronger, and Gurushyam Hariharan.
The UT Austin Villa 2003 Four-Legged Team.
In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, RoboCup-2003: Robot Soccer World Cup VII. Springer Verlag, Berlin, 2004.

29
Peter Stone.
ATTUnited-2001: Using Heterogeneous Players.
In Andreas Birk, Silvia Coradeschi, and Satoshi Tadokoro, editors, RoboCup-2001: Robot Soccer World Cup V, volume 2377 of Lecture Notes in Artificial Intelligence, pages 495–98. Springer Verlag, Berlin, 2002.

30
Patrick Riley, Peter Stone, David McAllester, and Manuela Veloso.
ATT-CMUnited-2000: Third place finisher in the RoboCup-2000 simulator league.
In P. Stone, T. Balch, and G. Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, volume 2019 of Lecture Notes in Artificial Intelligence. Springer Verlag, Berlin, 2001.

31
Peter Stone.
Layered learning in multi-agent systems.
Ph.D. thesis, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, December 1998. Technical Report CMU-CS-98-187.

32
Manuela Veloso, Hiroaki Kitano, Enrico Pagello, Gerhard Kraetzschmar, Peter Stone, Tucker Balch, Minoru Asada, Silvia Coradeschi, Lars Karlsson, and Masahiro Fujita.
Overview of RoboCup-99.
In M. Veloso, E. Pagello, and H. Kitano, editors, RoboCup-99: Robot Soccer World Cup III, volume 1856 of Lecture Notes in Artificial Intelligence, pages 1–34. Springer Verlag, Berlin, 2000.

33
Peter Stone, Patrick Riley, and Manuela Veloso.
The CMUnited-99 champion simulator team.
In M. Veloso, E. Pagello, and H. Kitano, editors, RoboCup-99: Robot Soccer World Cup III, volume 1856 of Lecture Notes in Artificial Intelligence, pages 35–48. Springer Verlag, Berlin, 2000.
Also in AI Magazine, 21(3), 2000.

34
Peter Stone, Manuela Veloso, and Patrick Riley.
The CMUnited-98 champion simulator team.
In M. Asada and H. Kitano, editors, RoboCup-98: Robot Soccer World Cup II, volume 1604 of Lecture Notes in Artificial Intelligence, pages 61–76. Springer Verlag, 1999.

35
Peter Stone and Manuela Veloso.
The CMUnited-97 simulator team.
In Hiroaki Kitano, editor, RoboCup-97: Robot Soccer World Cup I, volume 1395 of Lecture Notes in Artificial Intelligence, pages 387–397. Springer Verlag, Berlin, 1998.

36
Manuela Veloso, Peter Stone, Kwun Han, and Sorin Achim.
The CMUnited-97 small-robot team.
In Hiroaki Kitano, editor, RoboCup-97: Robot Soccer World Cup I, volume 1395 of Lecture Notes in Artificial Intelligence, pages 242–256. Springer Verlag, Berlin, 1998.
Also in AI Magazine, 19(3):61–69, 1998.

37
Emiel Corten, Klaus Dorer, Fredrik Heintz, Kostas Kostiadis, Johan Kummeneje, Helmut Myritz, Itsuki Noda, Patrick Riley, Peter Stone, and Travlex Yeap.
Soccer server manual, version 5.0.
Technical Report RoboCup-1999-001, RoboCup, 1999.

38
Gregg Rabideau, Steve Chien, Tobias Mann, Curt Eggemeyer, and Peter Stone.
DCAPS User's Manual.
Technical Document D-13741, Jet Propulsion Laboratory (JPL), 1996.




PROFESSIONAL MEMBERSHIPS




PRESS

Interviewed and quoted regarding research several times on television, on radio, and in magazines and newspapers including CNN, NPR, BBC, The New York Times, Wall Street Journal, USA Today, Pittsburgh Post-Gazette, Scientific American, and Austin American Statesman. Appeared on PBS Scientific American Frontiers hosted by Alan Alda.
Links to stories available at http://www.cs.utexas.edu/users/pstone/press.shtml




PERSONAL

Married, three children -- born 1998, 2000, 2002.
Citizenship: U.S.



Peter Stone
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