A multi-path compilation approach to contingent planning

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

    12 Scopus citations

    Abstract

    We describe a new sound and complete method for compiling contingent planning problems with sensing actions into classical planning. Our method encodes conditional plans within a linear, classical plan. This allows our planner, MPSR, to reason about multiple future outcomes of sensing actions, and makes it less susceptible to dead-ends. MPRS, however, generates very large classical planning problems. To overcome this, we use an incomplete variant of the method, based on state sampling, within an online replanner. On most current domains, MPSR finds plans faster, although its plans are often longer. But on a new challenging variant of Wumpus with dead-ends, it finds smaller plans, faster, and scales better.

    Original languageEnglish
    Title of host publicationAAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference
    Pages1868-1874
    Number of pages7
    StatePublished - 7 Nov 2012
    Event26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12 - Toronto, ON, Canada
    Duration: 22 Jul 201226 Jul 2012

    Publication series

    NameProceedings of the National Conference on Artificial Intelligence
    Volume3

    Conference

    Conference26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12
    Country/TerritoryCanada
    CityToronto, ON
    Period22/07/1226/07/12

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

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