Paper Info
Title
An Evolutionary Algorithm Coupled With The Hooke-Jeeves Algorithm For Tuning A Chess Evaluation Function
Abstract
In a previous paper presented at CEC'2011, we reported the implementation of a chess engine based on evolutionary programming with a selection mechanism that relied on grandmaster's chess games. The objective was to decide the virtual players that would pass to the following generation. Here, we use these same techniques to adjust a larger number of weights (29 in this work instead of the 5 used in the previous one). The aim was to improve the rating of our chess engine. We also introduce here the use of a local search scheme based on the Hooke-Jeeves algorithm, which is adopted to adjust the weights of the best virtual player obtained in the evolutionary process. As our results indicate, this produced a further improvement in the rating of our chess engine. As in our previous work, the material values of the additional pieces considered here are similar to the values known from chess theory.
Year
DOI
Venue
2012
10.1109/CEC.2012.6252977
2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
Keywords
Field
DocType
games,materials,evolutionary computation,evolutionary algorithm,programming,databases,engines,evolutionary programming
Chess theory,Evolutionary algorithm,Computer science,Turns, rounds and time-keeping systems in games,Evaluation function,Algorithm,Evolutionary computation,Transposition table,Artificial intelligence,Local search (optimization),Evolutionary programming,Machine learning
Conference
Citations 
PageRank 
References 
2
0.38
11
Authors
3
Name
Order
Citations
PageRank
Eduardo Vázquez-Fernández151.48
C. A. Coello Coello25799427.99
Feliu Davino Sagols Troncoso352.15