Designing an Evolutionary Strategizing Machine for Game Playing and Beyond

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  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 =          "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

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