Learning to Play the Game of Chess

Part of Advances in Neural Information Processing Systems 7 (NIPS 1994)

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Sebastian Thrun


This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial neural networks. It integrates inductive neural network learning, temporal differencing, and a variant of explanation-based learning. Performance results illustrate some of the strengths and weaknesses of this approach.