Towards rational deployment of multiple heuristics in A*

David Tolpin, Tal Beja, Solomon Eyal Shimony, Ariel Felner, Erez Karpas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

The obvious way to use several admissible heuristics in A* is to take their maximum. In this paper we aim to reduce the time spent on computing heuristics. We discuss Lazy A*, a variant of A* where heuristics are evaluated lazily: only when they are essential to a decision to be made in the A* search process. We present a new rational meta-reasoning based scheme, rational lazy A*, which decides whether to compute the more expensive heuristics at all, based on a myopic value of information estimate. Both methods are examined theoretically. Empirical evaluation on several domains supports the theoretical results, and shows that lazy A* and rational lazy A* are state-of-the-art heuristic combination methods.

Original languageEnglish
Title of host publicationIJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
Pages674-680
Number of pages7
StatePublished - 1 Dec 2013
Event23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China
Duration: 3 Aug 20139 Aug 2013

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Country/TerritoryChina
CityBeijing
Period3/08/139/08/13

ASJC Scopus subject areas

  • Artificial Intelligence

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