Machine Learning in Computer Chess: Genetic Programmig and KRK (2003)
by
David Gleich
| Citations: | 1 - 0 self |
BibTeX
@TECHREPORT{Gleich03machinelearning,
author = {David Gleich},
title = {Machine Learning in Computer Chess: Genetic Programmig and KRK},
institution = {},
year = {2003}
}
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Abstract
In this paper, I describe genetic programming as a machine learning paradigm and evaluate its results in attempting to learn basic chess rules. Genetic programming exploits a simulation of Darwinian evolution to construct programs. When applied to the King-Rook-King (KRK) chess endgame problem, genetic programming shows promising results in spite of a lack of significant chess knowledge.
