Factored planning: How, when, and when not

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

    70 Scopus citations

    Abstract

    Automated domain factoring, and planning methods that utilize them, have long been of interest to planning researchers. Recent work in this area yielded new theoretical insight and algorithms, but left many questions open: How to decompose a domain into factors? How to work with these factors? And whether and when decomposition-based methods are useful? This paper provides theoretical analysis that answers many of these questions: it proposes a novel approach to factored planning; proves its theoretical superiority over previous methods; provides insight into how to factor domains; and uses its novel complexity results to analyze when factored planning is likely to perform well, and when not. It also establishes the key role played by the domain's causal graph in the complexity analysis of planning algorithms.

    Original languageEnglish
    Title of host publicationProceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
    Pages809-814
    Number of pages6
    StatePublished - 13 Nov 2006
    Event21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06 - Boston, MA, United States
    Duration: 16 Jul 200620 Jul 2006

    Publication series

    NameProceedings of the National Conference on Artificial Intelligence
    Volume1

    Conference

    Conference21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
    Country/TerritoryUnited States
    CityBoston, MA
    Period16/07/0620/07/06

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

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