Title :
Designing an Evolutionary Strategizing Machine for Game Playing and Beyond
Author :
Sipper, Moshe ; Azaria, Yaniv ; Hauptman, Ami ; Shichel, Yehonatan
Author_Institution :
Ben-Gurion Univ., Beer-Sheva
fDate :
7/1/2007 12:00:00 AM
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.
Keywords :
computer games; genetic algorithms; backgammon; chess endgames; evolutionary strategizing machine; game playing; genetic programming; human intelligence; human-competitive strategies; robocode; tank-fight simulation; Ambient intelligence; Application software; Artificial intelligence; Computer science; Evolution (biology); Evolutionary computation; Genetic programming; Humans; Learning systems; Machine intelligence; Backgammon; chess; evolutionary algorithms; evolving game strategies; genetic programming; robocode; strategizing;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/TSMCC.2007.897326