Chess Player by Co-Evolutionary Algorithm
Neural and Evolutionary Computing
2016-05-24 v1
Abstract
A co-evolutionary algorithm (CA) based chess player is presented. Implementation details of the algorithms, namely coding, population, variation operators are described. The alpha-beta or mini-max like behaviour of the player is achieved through two competitive or cooperative populations. Special attention is given to the fitness function evaluation (the heart of the solution). Test results on algorithms vs. algorithms or human player is provided.
Keywords
Cite
@article{arxiv.1605.06710,
title = {Chess Player by Co-Evolutionary Algorithm},
author = {Nuno Ramos and Sergio Salgado and Agostinho C Rosa},
journal= {arXiv preprint arXiv:1605.06710},
year = {2016}
}
Comments
8 pages, 11 figures and 12 tables