Evolving both search and strategy for Reversi players using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Benbassat:2012:CIG,

• author = "Amit Benbassat and Moshe Sipper",
• title = "Evolving both search and strategy for {Reversi} players using genetic programming",
• booktitle = "IEEE Conference on Computational Intelligence and Games, CIG 2012",
• year = "2012",
• pages = "47--54",
• address = "Granada",
• month = "11-14 " # sep,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, computer games, search problems, trees (mathematics), Reversi players, deterministic board game, full-knowledge board game, game-tree pruning, search algorithm, selective directional crossover method, zero-sum board game, Games, Humans, Receivers, Sociology, Statistics",
• isbn13 = "978-1-4673-1193-9",
• URL = "https://bibtex.github.io/CIG-2012-BenbassatS.html",
• DOI = "doi:10.1109/CIG.2012.6374137",
• size = "8 pages",
• abstract = "We present the application of genetic programming to the zero-sum, deterministic, full-knowledge board game of Reversi. Expanding on our previous work on evolving boardstate evaluation functions, we now evolve the search algorithm as well, by allowing evolved programs control of game-tree pruning. We use strongly typed genetic programming, explicitly defined introns, and a selective directional crossover method. We show that our system regularly churns out highly competent players and our results prove easy to scale.",
• notes = "Also known as \cite{6374137}",

}

Genetic Programming entries for Amit Benbassat Moshe Sipper

Citations