Learning to Play the Game of Chess
Conference Paper, Proceedings of (NeurIPS) Neural Information Processing Systems, pp. 1069 - 1076, December, 1994
Abstract
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.
BibTeX
@conference{Thrun-1994-16113,author = {Sebastian Thrun},
title = {Learning to Play the Game of Chess},
booktitle = {Proceedings of (NeurIPS) Neural Information Processing Systems},
year = {1994},
month = {December},
editor = {G. Tesauro, D. Touretzky and T. Leen},
pages = {1069 - 1076},
publisher = {MIT Press.},
}
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