Best-first minimax search
نویسندگان
چکیده
منابع مشابه
Best-First Minimax Search
We describe a very simple selective search algorithm for two-player games, called best-first minimax. It always expands next the node at the end of the expected line of play, which determines the minimax value of the root. It uses the same information as alpha-beta minimax, and takes roughly the same time per node generation. We present an implementation of the algorithm that reduces its space ...
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We present a very simple selective minimax search algorithm for two-player gaines. It ahvays expands next the frontier node at the end of the principal variation, or current best line of play, which is the node that determines the minimax value of the root. The algorithm requires no information other than a static evaluation function, and its time overhead per node is similar to that of alpha-b...
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We describe a novel parallel randomized search algorithm for two-player games. The algorithm is a randomized version of Korf and Chickering’s best-first search. Randomization both fixes a defect in the original algorithm and introduces significant parallelism. An experimental evaluation demonstrates that the algorithm is efficient (in terms of the number of search-tree vertices that it visits) ...
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We present a very simple selective search algorithm for two-player games. It always expands next the frontier node that determines the minimax value of the root. The algorithm requires no information other than a static evaluation function, and its time overhead per node is similar to that of alpha-beta minimax. We also present an implementation of the algorithm that reduces its space complexit...
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Most practitioners use a variant of the Alpha-Beta algorithm, a simple depth-first procedure, for searching minimax trees. SSS*, with its best-first search strategy, reportedly offers the potential for more efficient search. However, the complex formulation of the algorithm and its alleged excessive memory requirements preclude its use in practice. For two decades, the search efficiency of “sma...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 1996
ISSN: 0004-3702
DOI: 10.1016/0004-3702(95)00096-8