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Multi-agent path finding with deadlines

  • Hang Ma
  • , Glenn Wagner
  • , Ariel Felner
  • , Jiaoyang Li
  • , T. K. Satish Kumar
  • , Sven Koenig

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

    51 Scopus citations

    Abstract

    We formalize Multi-Agent Path Finding with Deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their given start vertices within the deadline, without colliding with each other. We first show that MAPF-DL is NP-hard to solve optimally. We then present two classes of optimal algorithms, one based on a reduction of MAPF-DL to a flow problem and a subsequent compact integer linear programming formulation of the resulting reduced abstracted multi-commodity flow network and the other one based on novel combinatorial search algorithms. Our empirical results demonstrate that these MAPF-DL solvers scale well and each one dominates the other ones in different scenarios.

    Original languageEnglish
    Title of host publicationProceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
    EditorsJerome Lang
    PublisherInternational Joint Conferences on Artificial Intelligence
    Pages417-423
    Number of pages7
    ISBN (Electronic)9780999241127
    DOIs
    StatePublished - 1 Jan 2018
    Event27th International Joint Conference on Artificial Intelligence, IJCAI 2018 - Stockholm, Sweden
    Duration: 13 Jul 201819 Jul 2018

    Publication series

    NameIJCAI International Joint Conference on Artificial Intelligence
    Volume2018-July
    ISSN (Print)1045-0823

    Conference

    Conference27th International Joint Conference on Artificial Intelligence, IJCAI 2018
    Country/TerritorySweden
    CityStockholm
    Period13/07/1819/07/18

    ASJC Scopus subject areas

    • Artificial Intelligence

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