Evolving Lose-Checkers Players using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Benbassat:2010:CIGPU,

• author = "Amit Benbassat and Moshe Sipper",
• title = "Evolving Lose-Checkers Players using Genetic Programming",
• booktitle = "IEEE Conference on Computational Intelligence and Game",
• year = "2010",
• pages = "30--37",
• address = "IT University of Copenhagen, Denmark",
• month = "18-21 " # aug,
• keywords = "genetic algorithms, genetic programming, explicitly defined intron, full knowledge board game, genetic programming tree, local mutation, lose checker player, multitree individual, state evaluator, computer games, trees (mathematics)",
• URL = "http://game.itu.dk/cig2010/proceedings/papers/cig10_005_011.pdf",
• DOI = "doi:10.1109/ITW.2010.5593376",
• size = "8 pages",
• 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 multitree 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.",
• notes = "http://game.itu.dk/cig2010/proceedings/wp-content/acceptedpapers.html Also known as \cite{5593376}",

}

Genetic Programming entries for Amit Benbassat Moshe Sipper

Citations