MM: A bidirectional search algorithm that is guaranteed to meet in the middle

Robert C. Holte, Ariel Felner, Guni Sharon, Nathan R. Sturtevant, Jingwei Chen

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Bidirectional search algorithms interleave two separate searches, a normal search forward from the start state, and a search backward from the goal. It is well known that adding a heuristic to unidirectional search dramatically reduces the search effort. By contrast, despite decades of research, bidirectional heuristic search has not yet had a major impact. Additionally, no comprehensive theory was ever devised to understand the nature of bidirectional heuristic search. In this paper we aim to close this gap. We first present MM, a novel bidirectional heuristic search algorithm. Unlike previous bidirectional heuristic search algorithms, MM's forward and backward searches are guaranteed to “meet in the middle”, i.e. never expand a node beyond the solution midpoint. Based on this unique attribute we present a novel framework for comparing MM, A*, and their brute-force variants. We do this by dividing the entire state space into disjoint regions based on their distance from the start and goal. This allows us to perform a comparison of these algorithms on a per region basis and identify conditions favoring each algorithm. Finally, we present experimental results that support our theoretical analysis.

Original languageEnglish
Pages (from-to)232-266
Number of pages35
JournalArtificial Intelligence
Volume252
DOIs
StatePublished - 1 Nov 2017

Keywords

  • Bidirectional search
  • Heuristic search

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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