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A Formal Metareasoning Model of Concurrent Planning and Execution

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

    4 Scopus citations

    Abstract

    Agents that plan and act in the real world must deal with the fact that time passes as they are planning. When timing is tight, there may be insufficient time to complete the search for a plan before it is time to act. By commencing execution before search concludes, one gains time to search by making planning and execution concurrent. However, this incurs the risk of making incorrect action choices, especially if actions are irreversible. This tradeoff between opportunity and risk is the problem addressed in this paper. Our main contribution is to formally define this setting as an abstract metareasoning problem. We find that the abstract problem is intractable. However, we identify special cases that are solvable in polynomial time, develop greedy solution algorithms, and, through tests on instances derived from search problems, find several methods that achieve promising practical performance. This work lays the foundation for a principled time-aware executive that concurrently plans and executes.

    Original languageEnglish
    Title of host publicationAAAI-23 Technical Tracks 10
    EditorsBrian Williams, Yiling Chen, Jennifer Neville
    PublisherAAAI press
    Pages12427-12435
    Number of pages9
    ISBN (Electronic)9781577358800
    DOIs
    StatePublished - 27 Jun 2023
    Event37th AAAI Conference on Artificial Intelligence, AAAI 2023 - Washington, United States
    Duration: 7 Feb 202314 Feb 2023

    Publication series

    NameProceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023
    Volume37

    Conference

    Conference37th AAAI Conference on Artificial Intelligence, AAAI 2023
    Country/TerritoryUnited States
    CityWashington
    Period7/02/2314/02/23

    ASJC Scopus subject areas

    • Artificial Intelligence

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