Designing an Evolutionary Strategizing Machine for Game Playing and Beyond

Authors:
M. Sipper;Y. Azaria;A. Hauptman;Y. Shichel
Affiliations:
Ben-Gurion Univ., Beer-Sheva;-;-;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Year:
2007

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Abstract

We have 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 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 strategizing machine.