Distributed game-tree search using transposition table driven work scheduling

Akihiro Kishimoto, J. Schaeffer
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引用次数: 21

Abstract

The /spl alpha//spl beta/ algorithm for two-player game-tree search has a notorious reputation as being a challenging algorithm for achieving reasonable parallel performance. MTD(f), a new /spl alpha//spl beta/ variant, has become the sequential algorithm of choice for practitioners. Unfortunately, MTD(f) inherits most of the parallel obstacles of /spl alpha//spl beta/, as well as creating new performance hurdles. Transposition-table-driven scheduling (TDS) is a new parallel search algorithm that has proven to be effective in the single-agent (one-player) domain. This paper presents TDSAB, the first time TDS parallelism has been applied to two-player search (the MTD(f) algorithm). Results show that TDSAB gives comparable speedups to that achieved by conventional parallel /spl alpha//spl beta/ algorithms. However, since this is a parallelization of a superior sequential algorithm the results in fact are better. This paper shows that the TDS idea can be extended to more challenging search domains.
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使用换位表驱动的分布式游戏树搜索工作调度
用于双人游戏树搜索的/spl alpha//spl beta/算法因为是实现合理并行性能的具有挑战性的算法而臭名昭著。MTD(f)是一种新的/spl alpha//spl beta/变体,已成为实践者选择的顺序算法。不幸的是,MTD(f)继承了/spl alpha//spl beta/的大部分并行障碍,并产生了新的性能障碍。换位表驱动调度(TDS)是一种新的并行搜索算法,已被证明在单智能体(一人)领域是有效的。本文提出了TDSAB算法,首次将TDS并行性应用于双玩家搜索(MTD(f)算法)。结果表明,TDSAB的加速速度与传统的并行/spl alpha//spl beta/算法相当。然而,由于这是一种优越的顺序算法的并行化,结果实际上更好。本文表明,TDS思想可以扩展到更具挑战性的搜索领域。
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