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Iterative-deepening Bidirectional Heuristic Search with Restricted Memory

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

    7 Scopus citations

    Abstract

    The field of bidirectional heuristic search has recently seen great advances. However, the subject of memory-restricted bidirectional search has not received recent attention. In this paper we introduce a general iterative deepening bidirectional heuristic search algorithm (IDBiHS) that searches simultaneously in both directions while controlling the meeting point of the search frontiers. First, we present the basic variant of IDBiHS, whose memory is linear in the search depth. We then add improvements that exploit consistency and front-to-front heuristics. Next, we move to the case where a fixed amount of memory is available to store nodes during the search and develop two variants of IDBiHS: (1) A+IDBiHS, that starts with Aand moves to IDBiHS as soon as memory is exhausted. (2) A variant that stores partial forward frontiers until memory is exhausted and then tries to match each of them from the backward side. Finally, we experimentally compare the new algorithms to existing unidirectional and bidirectional ones. In many cases our new algorithms outperform previous ones in both node expansions and time.

    Original languageEnglish
    Title of host publication31st International Conference on Automated Planning and Scheduling, ICAPS 2021
    EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
    PublisherAssociation for the Advancement of Artificial Intelligence
    Pages331-339
    Number of pages9
    ISBN (Electronic)9781713832317
    DOIs
    StatePublished - 1 Jan 2021
    Event31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China
    Duration: 2 Aug 202113 Aug 2021

    Publication series

    NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
    Volume2021-August
    ISSN (Print)2334-0835
    ISSN (Electronic)2334-0843

    Conference

    Conference31st International Conference on Automated Planning and Scheduling, ICAPS 2021
    Country/TerritoryChina
    CityGuangzhou, Virtual
    Period2/08/2113/08/21

    ASJC Scopus subject areas

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

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