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A Neural Coach for Teaching Robots Using Diagrams

In this paper we show how to train soccer robots using static game situations in diagrams arranged by a human coach. Rather than programming every detail by hand, we let the robots learn from strategic examples sketched by the coach. With our approach, the coach defines new game positions and indicates to the players how to react to them, like in real soccer. We have implemented a management tool to collect and organize all the game positions entered by the coach. The game situation is encoded as a feature vector, which is used to train a neural network. The network learn to generalize and give advice on the best option for a player. The general method is illustrated with the specific case of robots learning to pass. The method can be generalized to other tasks and to several networks encoding different game strategies.