多状态承诺搜索

Y. Kitamura, M. Yokoo, T. Miyaji, S. Tatsumi
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引用次数: 10

摘要

我们提出了多状态承诺(MSC)方法来加速半最优解的启发式搜索算法。实时A* (RTA*)和加权A* (WA*)是半最优解的代表性启发式搜索算法,可分别视为单状态承诺搜索算法和全状态承诺搜索算法。在这些算法中,在搜索过程中做出错误选择的风险和用于恢复的内存量之间存在权衡,RTA*和WA*是极端情况。MSC方法在这些算法中引入了适度和灵活的特性,可以显著提高算法在求解n谜题等问题中的性能。在本文中,通过引入一个提交列表,我们展示了RTA*和WA*在不违反其完整性的情况下对其MSC版本的修改。然后,我们对它们在迷宫和n -谜题问题中的性能进行了实验,并讨论了MSC方法有效的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-state commitment search
We propose the multi-state commitment (MSC) method to speed-up heuristic search algorithms for semi-optimal solutions. The real-time A* (RTA*) and the weighted A* (WA*) are representative heuristic search algorithms for semi-optimal solutions and can be viewed as single-state and an all-state commitment search algorithms respectively. In these algorithms, there is a tradeoff between the risk of making wrong choices in search process and the amount of memory for the recovery, with RTA* and WA* being the extremes. The MSC method introduces a moderate and flexible characteristic into these algorithms and can increase the performance dramatically in problems such as the N-puzzle. In this paper, by introducing a commitment-list, we show a modification of RTA* and WA* to their MSC versions without violating their completeness. Then, we experiment with their performance in maze and N-puzzle problems, and discuss conditions that the MSC method is effective.
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