Dynamic potential search – a new bounded suboptimal search algorithm

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    28 Scopus citations

    Abstract

    Potential Search (PS) is an algorithm that is designed to solve bounded cost search problems. In this paper, we modify PS to work within the framework of bounded suboptimal search and introduce Dynamic Potential Search (DPS). DPS uses the idea of PS but modifies the bound to be the product of the minimal f-value in OPEN and the required suboptimal bound. We study DPS and its attributes. We then experimentally compare DPS to WA* and to EES on a variety of domains and study parameters that affect the behavior of these algorithms. In general we show that in domains with unit edge costs (e.g., many standard benchmarks) DPS significantly outperforms WA* and EES but there are exceptions.

    Original languageEnglish
    Title of host publicationProceedings of the 9th Annual Symposium on Combinatorial Search, SoCS 2016
    EditorsJorge A. Baier, Adi Botea
    PublisherAAAI press
    Pages36-44
    Number of pages9
    ISBN (Electronic)9781577357698
    StatePublished - 1 Jan 2016
    Event9th Annual Symposium on Combinatorial Search, SoCS 2016 - Tarrytown, United States
    Duration: 6 Jul 20168 Jul 2016

    Publication series

    NameProceedings of the 9th Annual Symposium on Combinatorial Search, SoCS 2016
    Volume2016-January

    Conference

    Conference9th Annual Symposium on Combinatorial Search, SoCS 2016
    Country/TerritoryUnited States
    CityTarrytown
    Period6/07/168/07/16

    ASJC Scopus subject areas

    • Computer Networks and Communications

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