Designing an Evolutionary Strategizing Machine for Game Playing and Beyond

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@Article{sipper:2007:SMC,

• title = "Designing an Evolutionary Strategizing Machine for Game Playing and Beyond",
• author = "Moshe Sipper and Yaniv Azaria and Ami Hauptman and Yehonatan Shichel",
• journal = "IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews",
• year = "2007",
• volume = "37",
• number = "4",
• month = jul,
• pages = "583--593",
• keywords = "genetic algorithms, genetic programming, Backgammon, chess, evolutionary algorithms, evolving game strategies, robocode, strategising",
• ISSN = "1094-6977",
• DOI = "10.1109/TSMCC.2007.897326",
• abstract = "We have recently shown that genetically programming game players, after having imbued the evolutionary process with human intelligence, produces human-competitive strategies for three games: backgammon, chess endgames, and robocode (tank-fight simulation). Evolved game players are able to hold their own and often win against human or human-based competitors. This paper has a twofold objective: first, to review our recent results of applying genetic programming in the domain of games; second, to formulate the merits of genetic programming in acting as a tool for developing strategies in general, and to discuss the possible design of a strategising machine.",

}

Genetic Programming entries for Moshe Sipper Yaniv Azaria Ami Hauptman Yehonatan Shichel

Citations