The evolution of subtle manoeuvres in simulated hockey

A simulated hockey environment is introduced as a test bed for studying adaptive behavior and evolution of robot controllers. A near-frictionless playing surface is employed, partially mimicking zero gravity conditions. We show how a neural network using a simple evolutionary algorithm can develop nimble strategies for moving about the rink and scoring goals quickly and effectively.