Evolving Lose-Checkers players using genetic programming

Amit Benbassat, Moshe Sipper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

We present the application of genetic programming (GP) to the zero-sum, deterministic, full-knowledge board game of Lose Checkers. Our system implements strongly typed GP trees, explicitly defined introns, local mutations, and multi-tree individuals. Explicitly defined introns in the genome allow for information selected out of the population to be kept as a reservoir for possible future use. Multi-tree individuals are implemented by a method inspired by structural genes in living organisms, whereby we take a single tree describing a state evaluator and split it.

Original languageEnglish
Title of host publicationProceedings of the 2010 IEEE Conference on Computational Intelligence and Games, CIG2010
Pages30-37
Number of pages8
DOIs
StatePublished - 1 Dec 2010
Event2010 IEEE Conference on Computational Intelligence and Games, CIG2010 - Copenhagen, Denmark
Duration: 18 Aug 201021 Aug 2010

Publication series

NameProceedings of the 2010 IEEE Conference on Computational Intelligence and Games, CIG2010

Conference

Conference2010 IEEE Conference on Computational Intelligence and Games, CIG2010
Country/TerritoryDenmark
CityCopenhagen
Period18/08/1021/08/10

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