Evolving board-game players with genetic programming

Amit Benbassat, Moshe Sipper

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

16 Scopus citations

Abstract

We present the application of genetic programming (GP) to zero-sum, deterministic, full-knowledge board games. Our work expands previous results in evolving board-state evaluation functions for Lose Checkers to a 10x10 variant of Checkers, as well as Reversi. Our system implements strongly typed GP trees, explicitly defined introns, and a selective directional crossover method.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication
Pages739-742
Number of pages4
DOIs
StatePublished - 26 Aug 2011
Event13th Annual Genetic and Evolutionary Computation Conference, GECCO'11 - Dublin, Ireland
Duration: 12 Jul 201116 Jul 2011

Publication series

NameGenetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication

Conference

Conference13th Annual Genetic and Evolutionary Computation Conference, GECCO'11
Country/TerritoryIreland
CityDublin
Period12/07/1116/07/11

Keywords

  • alpha-beta search
  • board games
  • games
  • genetic programming

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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