Peter Stone
Professor
Dr. Peter Stone's main research interest in AI is understanding how we can best create complete intelligent agents. He considers adaptation, interaction, and embodiment to be essential capabilities of such agents. Thus, his research focuses mainly on machine learning, multiagent systems, and robotics. For him, the most exciting research topics are those inspired by challenging real-world problems. He believes that complete, successful research includes both precise, novel algorithms and fully implemented and rigorously evaluated applications. His application domains have included robot soccer, autonomous bidding agents, autonomous vehicles, autonomic computing, and social agents.
Research
Research Areas:
Research Interests:
- Reinforcement Learning
- Multiagent Systems
- Robotics
- Multiagent Learning
- AI Planning
Current Research:
View complete list of current research topics.
Research Labs & Affiliations:
Select Publications
. 2018. Overlapping Layered Learning. Artificial Intelligence Journal.254:21–43.
. 2018. Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems. Artificial Intelligence Journal.258:66–95.
. 2017. BWIBots: A platform for bridging the gap between AI and human--robot interaction research. International Journal of Robotics Research.36: 635-659 .
. 2017. Network-wide Adaptive Tolling for Connected and Automated vehicles. ransportation Research Part C.84:142–157.
. 2013. TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. Machine Learning Journal.90(3):385–429.
Awards & Honors
- 2019 - AAAS Fellow
- 2019 - Minnie Stevens Piper Professorship
- 2018 - IEEE Fellow
- 2016 - ACM/SIGAI Autonomous Agents Research Award
- 2012 - AAAI Fellow
- 2008 - Guggenheim Fellow
- 2008 - Fulbright Award
- 2008 - William David Blunk Memorial Professorship
- 2007 - IJCAI Computers and Thought Award
- 2004 - Alfred P. Sloan Research Fellow
Contact Info
Peter Stone
Truchard Foundation Chair in Computer Science and University Distinguished Teaching Professor
(512) 471-9796
GDC 3.508