Why does the adversarial search minimax algorithm use Depth-First Search (DFS) instead of Breadth-First Search (BFS)?
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?
Why do neural nets and machine learning tend to work well with MCTS, but not with regular Minimax game-playing AI?
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