Deordering and numeric macro actions for plan repair

Enrico Scala, Pietro Torasso

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

    19 Citations (Scopus)

    Abstract

    The paper faces the problem of plan repair in presence of numeric information, by providing a new method for the intelligent selection of numeric macro actions. The method relies on a generalization of deordering, extended with new conditions accounting for dependencies and threats implied by the numeric components. The deordering is used as a means to infer (hopefully) minimal ordering constraints then used to extract independent and informative macro actions. Each macro aims at compactly representing a sub-solution for the overall planning problem. To verify the feasibility of the approach, the paper reports experiments in various domains from the International Planning Competition. Results show (i) the competitiveness of the strategy in terms of coverage, time and quality of the resulting plans wrt current approaches, and (ii) the actual independence from the planner employed.

    Original languageEnglish
    Title of host publicationIJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence
    EditorsMichael Wooldridge, Qiang Yang
    PublisherInternational Joint Conferences on Artificial Intelligence
    Pages1673-1681
    Number of pages9
    ISBN (Electronic)9781577357384
    Publication statusPublished - 2015
    Event24th International Joint Conference on Artificial Intelligence, IJCAI 2015 - Buenos Aires, Argentina
    Duration: 25 Jul 201531 Jul 2015

    Publication series

    NameIJCAI International Joint Conference on Artificial Intelligence
    Volume2015-January
    ISSN (Print)1045-0823

    Conference

    Conference24th International Joint Conference on Artificial Intelligence, IJCAI 2015
    Country/TerritoryArgentina
    CityBuenos Aires
    Period25/07/1531/07/15

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