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

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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.

Original languageEnglish
Article number130647
JournalProceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS
Volume35
DOIs
Publication statusPublished - 4 May 2022
Event35th International Florida Artificial Intelligence Research Society Conference, FLAIRS-35 2022 - Jensen Beach, United States
Duration: 15 May 202218 May 2022

Keywords

  • factored planning
  • multi-agent planning
  • multi-robot planning
  • system architectures
  • task planning

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