A genetic minimax game-playing strategy

The authors consider the problem of finding good next moves in two-player games. Traditional search algorithms, such as minimax and α-β pruning suffer great temporal and spatial expansion when exploring deeply into search trees to find better next moves. The evolution of genetic algorithms, abilities to find global or near global optima in limited times seems promising, but they are inept at finding compound optima such as the minimax in a game search tree. They propose a new genetic-algorithm-based approach that can find a good next move by reserving the board evaluation values of new offspring in a partial game-search tree. Experiments show that solution accuracy and search speed are greatly improved by the algorithms