197: TZ Interview - Peter Stone / Robot Soccer and Multiagent Learning

19/07/2012 1h 1min
197: TZ Interview - Peter Stone / Robot Soccer and Multiagent Learning

Listen "197: TZ Interview - Peter Stone / Robot Soccer and Multiagent Learning"

Episode Synopsis

Jason talks with Peter Stone, director of the Learning Agents Research Group at UT Austin, whose team, UT Austin Villa, won both the standard platform league and the 3D simulation league of the RoboCup 2012 competition. They discuss why robot soccer is a good motivating application domain for machine learning, how the RoboCup competition got started and the kinds of teams that participate, the offshoot competition RoboCup Jr, why the machine learning technique known as reinforcement learning works so well in complex, dynamic environments, the role played by game theory in multiagents systems, Peter's involvement in developing autonomous driving vehicles and what it's like to run an artificial intelligence laboratory.