Simulated RoboCup Soccer (2004)
The UT Austin Villa Robot Soccer Team has been very active in international RoboCup competitions for the past several years, and have therefore built up a great deal of expertise in the domain of Robot Soccer and the subtask of keepaway. Reinforcement Learning often plays an important role in the success of these soccer players. Links to several demo pages associated with Robot Soccer are provided below.

Keepaway
Keepaway Pass+GetOpen
Half Field Offense
People
Peter Stone Faculty pstone [at] cs utexas edu
Shivaram Kalyanakrishnan Ph.D. Alumni shivaram [at] cs utexas edu
Gregory Kuhlmann Ph.D. Alumni kuhlmann [at] cs utexas edu
Matthew Taylor Ph.D. Alumni taylorm [at] eecs wsu edu
Projects
The UT Austin Villa Robot Soccer team 2003 - Present
Publications
Learning Complementary Multiagent Behaviors: A Case Study 2009
Shivaram Kalyanakrishnan and Peter Stone, In Proceedings of the RoboCup International Symposium 2009 2009. Springer Verlag.
Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study 2007
Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 72-85, Berlin 2007. Springer Verlag.
Keepaway Soccer: From Machine Learning Testbed to Benchmark 2006
Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu, In RoboCup-2005: Robot Soccer World Cup IX, Itsuki Noda and Adam Jacoff and Ansgar Bredenfeld and Yasutake Takahashi (Eds.), Vol. 4020, pp. 93-105, Berlin 2006. Springer Verlag.
Reinforcement Learning for RoboCup-Soccer Keepaway 2005
Peter Stone, Richard S. Sutton, and Gregory Kuhlmann, Adaptive Behavior, Vol. 13, 3 (2005), pp. 165-188.
RoboCup as an Introduction to CS Research 2004
Peter Stone, In RoboCup-2003: Robot Soccer World Cup VII, Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida (Eds.), Vol. 3020, pp. 284-95, Berlin 2004. Springer Verlag.
Software/Data
Keepaway player framework source code, version 0.6 The Keepaway player framework is an implementation of all the low- and mid-level keepaway behaviors described in the pub...
Related Areas
Multiagent Systems Reinforcement Learning RoboCup Robot Soccer
Labs
Learning Agents