Evolving Lose-Checkers Players using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Benbassat:2010:CIGPU,
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author = "Amit Benbassat and Moshe Sipper",
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title = "Evolving Lose-Checkers Players using Genetic
Programming",
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booktitle = "IEEE Conference on Computational Intelligence and
Game",
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year = "2010",
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pages = "30--37",
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address = "IT University of Copenhagen, Denmark",
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month = "18-21 " # aug,
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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)",
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URL = "http://game.itu.dk/cig2010/proceedings/papers/cig10_005_011.pdf",
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DOI = "doi:10.1109/ITW.2010.5593376",
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size = "8 pages",
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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.",
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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