EgoPlan : A framework for multi-agent planning using single agent planners

McArthur, Mark and Moshfeghi, Yashar and Cashmore, Michael (2022) EgoPlan : A framework for multi-agent planning using single agent planners. Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS, 35. 130647. ISSN 2334-0762 (https://doi.org/10.32473/flairs.v35i.130647)

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Abstract

Planning problems are, in general, PSPACE-complete; large problems, especially multi-agent problems with required coordination, can be intractable or impractical to solve. Factored planning and multi-agent planning both address this by separating multi-agent problems into tractable sub-problems, but there are limitations in the expressivity of existing planners and in the ability to handle tightly coupled multi-agent problems. This paper presents EGOPLAN, a framework which factors a multi-agent problem into related sub-problems which are solved by iteratively calling on a single agent planner. EGOPLAN is evaluated on a multi-robot test domain with durative actions, required coordination, and temporal constraints, comparing the performance of a temporal planner, OPTIC-CPLEX, with and without EGOPLAN. Our results show that for our test domain, using EGOPLAN allows OPTIC-CPLEX to solve problems that are twice as complex as it can solve without EGOPLAN, and to solve complex problems significantly faster.

ORCID iDs

McArthur, Mark, Moshfeghi, Yashar and Cashmore, Michael ORCID logoORCID: https://orcid.org/0000-0002-8334-4348;
  • Item type:Article
    ID code:81372
    Dates:
    Date
    Event
    4 May 2022
    Published
    28 March 2022
    Accepted
    Keywords:factored planning, multi-agent planning, multi-robot planning, system architectures, task planning, Electronic computers. Computer science, Artificial Intelligence, Software
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:06 Jul 2022 14:11
    Last modified:25 Nov 2023 02:42
    URI:https://strathprints.strath.ac.uk/id/eprint/81372
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