Using Lookaheads with Optimal Best-First Search

被引：0

作者：

Stern, Roni ^{[1
]}

Kulberis, Tamar ^{[1
]}

Felner, Ariel ^{[1
]}

Holte, Robert ^{[2
]}

机构：

[1] Ben Gurion Univ Negev, Informat Syst Engn, Deutsch Telekom Labs, IL-85104 Beer Sheva, Israel

[2] Univ Alberta, Dept Comp Sci, Edmonton, AB T6G 2E8, Canada

来源：

PROCEEDINGS OF THE TWENTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-10) | 2010年

基金：

加拿大自然科学与工程研究理事会;

关键词：

HEURISTIC-SEARCH;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present an algorithm that exploits the complimentary benefits of best-first search (BFS) and depth-first search (DFS) by performing limited DFS lookaheads from the frontier of BFS. We show that this continuum requires significantly less memory than BFS. In addition, a time speedup is also achieved when choosing the lookahead depth correctly. We demonstrate this idea for breadth-first search and for A*. Additionally, we show that when using inconsistent heuristics, Bidirectional Pathmax (BPMX), can be implemented very easily on top of the lookahead phase. Experimental results on several domains demonstrate the benefits of all our ideas.

引用

页码：185 / 190

页数：6

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