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

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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 ORCID logoORCID: https://orcid.org/0000-0003-4186-1088 and Cashmore, Michael ORCID logoORCID: https://orcid.org/0000-0002-8334-4348;
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