Game trees are important in artificial intelligence because one way to pick the best move in a game is to search the game tree using the minimax algorithm or its variants.
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Since the minimax algorithm and its variants are inherently iterative deepening is usually used in conjunction with alpha beta so that a reasonably good move can be returned even if the algorithm is interrupted before it has finished execution.
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In competitive two-player games, the "'killer heuristic "'is a technique for improving the efficiency of alpha-beta pruning, which in turn improves the efficiency of the minimax algorithm.
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He worked with Wim Pijls on a new best-first minimax algorithm named SSS *, and in 1994 the pair showed a link with the well-known Alpha-beta algorithm at a symposium at Maastricht University.
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A "'minimax algorithm "'is a recursive algorithm for choosing the next move in an n-player position evaluation function and it indicates how good it would be for a player to reach that position.
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Alpha-beta pruning speeds the minimax algorithm by identifying " cutoffs ", points in the game tree where the current position is so good for the side to move that best play by the other side would have avoided it.
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