Evolving players that use selective game-tree search with genetic programming

Amit Benbassat, Moshe Sipper

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

2 Scopus citations

Abstract

We present the application of genetic programming (GP) to evolving game-tree search in board games. Our work expands previous results in evolving board-state evaluation functions for multiple board games, now evolving a search-guiding evaluation function alongside it. Our system implements strongly typed GP trees, explicitly defined introns, and a selective directional crossover method. Copyright is held by the author/owner(s).

Original languageEnglish
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion
PublisherAssociation for Computing Machinery
Pages631-632
Number of pages2
ISBN (Print)9781450311786
DOIs
StatePublished - 1 Jan 2012
Event14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion - Philadelphia, PA, United States
Duration: 7 Jul 201211 Jul 2012

Publication series

NameGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion

Conference

Conference14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion
Country/TerritoryUnited States
CityPhiladelphia, PA
Period7/07/1211/07/12

Keywords

  • Alpha-beta search
  • Board games
  • Games
  • Genetic programming

ASJC Scopus subject areas

  • Computational Theory and Mathematics

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