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Leaf-Value Tables for Pruning Non-Zero-Sum Games

机译:修剪非零和游戏的叶值表

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摘要

Algorithms for pruning game trees generally rely on a game being zero-sum, in the case of alpha-beta pruning, or constant-sum, in the case of multi-player pruning algorithms such as speculative pruning. While existing algorithms can prune non-zero-sum games, pruning is much less effective than in constant-sum games. We introduce the idea of leaf-value tables, which store an enumeration of the possible leaf values in a game tree. Using these tables we are can make perfect decisions about whether or not it is possible to prune a given node in a tree. Leaf-value tables also make it easier to incorporate monotonic heuristics for increased pruning. In the 3-player perfect-information variant of Spades we are able to reduce node expansions by two orders of magnitude over the previous best zero-sum and non-zero-sum pruning techniques.
机译:修剪游戏树的算法通常依赖于游戏,在alpha-beta修剪情况下,游戏为零和,在多玩家修剪算法(例如推测性修剪)情况下,为常数和。尽管现有算法可以修剪非零和游戏,但修剪比固定和游戏要有效得多。我们介绍了叶值表的概念,该表存储游戏树中可能的叶值的枚举。使用这些表,我们可以做出关于是否可以修剪树中给定节点的完美决策。叶值表还使合并单调启发式方法变得更加容易,以增加修剪效果。在Spades的3人完美信息变体中,我们能够将节点扩展比以前的最佳零和和非零和修剪技术减少两个数量级。

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