Off-line learning of soccer formations from game logs

In RoboCup Soccer Simulation 2D League, it is often difficult for players to make a correct decision because of the uncertainty in the field information. We particularly focus on the unpredictability of the opponent player´s position. This paper presents a method that learns opponent team formation. Neural networks are used for this purpose. In the computational experiments of this paper, we show that team formation is successfully learned by neural networks. We also show the application of the learned neural networks to the prediction of successful passes.