Predicting the effectiveness of bidirectional heuristic search

Nathan R. Sturtevant, Shahaf Shperberg, Ariel Felner, Jingwei Chen

Research output: Contribution to journalConference articlepeer-review

Abstract

The question of when bidirectional heuristic search outperforms unidirectional heuristic search has been revisited numerous times in the field of Artificial Intelligence. This paper re-addresses the question of when bidirectional search outperforms unidirectional search using an updated theoretical understanding of the problem. We show that a core set of critical states in the state space are the primary factor determining whether a bidirectional search can outperform a unidirectional search and provide simple measures to determine whether a state space and heuristic contains these critical states. We similarly discuss and show the impact that asymmetry in the underlying problem graph has on the performance of bidirectional algorithms. Experimental results show the impact of these factors on whether a problem should be solved using unidirectional or bidirectional search.

Original languageEnglish
Pages (from-to)281-290
Number of pages10
JournalProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume30
StatePublished - 29 May 2020
Event30th International Conference on Automated Planning and Scheduling, ICAPS 2020 - Nancy, France
Duration: 26 Oct 202030 Oct 2020

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management

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