Abstract

It is well known that when exploring a game tree, the deeper the depth, the more accurate the move prediction but greater temporal and spatial expansion is required. How to explore the game tree deeper is a great challenge in such research. In T.P. Hong et al (Int. Conf. on Evolutionary Computation, Anchorage, Alaska, USA, p.690-4, 1998), we proposed a genetic algorithm-based search method for two-player games. In this paper, we generalize that method to solve multi-player game-search problems. We propose a genetic algorithm-based approach that can find good next moves in multi-player games without the requirement for great temporal and spatial expansion.

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