Using Distance Estimates in Heuristic Search
Using Distance Estimates in Heuristic Search
复制标题
在启发式搜索中使用距离估计
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Wheeler Ruml
中科院分区：
文献类型：
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作者：
J. Thayer;Wheeler Ruml
本文探讨了经常登记的信息源在启发式搜索中：搜索距离的估计值经常具有不同的成本，而成本范围与搜索范围不一样特别是在某些临时计划中，我们显示了如何将距离估算到加权a*中，并在几个域中提高其性能。
This paper explores the use of an oft-ignored information source in heuristic search: a search-distance-to-go estimate. Operators frequently have different costs and cost-to-go is not the same as search-distance-to-go. We evaluate two previous proposals: dynamically weighted A* and A* epsilon. We present a revision to dynamically weighted A* that improves its performance substantially in domains where the search does not progress uniformly towards solutions, and particularly in certain temporal planning problems. We show how to incorporate distance estimates into weighted A* and improve its performance in several domains. Both approaches lead to dramatic performance increases in popular benchmark domains.