Learning to Play the Game of Chess

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.

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@INPROCEEDINGS{Thrun95a,
  AUTHOR         = {S. Thrun},
  YEAR           = {1995},
  TITLE          = {Learning to Play the Game of Chess},
  BOOKTITLE      = {Advances in Neural Information Processing Systems 
                    (NIPS) 7},
  EDITOR         = {G. Tesauro and D. Touretzky and T. Leen},
  PUBLISHER      = {MIT Press},
  ADDRESS        = {Cambridge, MA}
}