A Scene-based Imitation Framework for RoboCup Clients

We describe an effort to train a RoboCup soccer-playing agent playing in the Simulation League by capturing data from existing players, and using it in a real-time scene recognition system. When observing a simple rule-based, stateless agent, the trained player appears to imitate the behaviour of the original. Apart from some parameter selections, the process requires little human intervention.