More effective way to improve the heuristics of an AI... evolution or testing between thousands of pre-determined sets of heuristics?
Could you share with me the tree size, search time and search depth of your implementation of Gomoku with minimax and alpha-beta prunning?
To deal with infinite loops, should I do a deeper search of the best moves with the same value, in alpha-beta pruning?
Are iterative deepening, principal variation search or quiescence search extensions of alpha-beta pruning?
How do I use a genetic algorithm to generate the scores of an evaluation function for alpha-beta pruning?
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