EgoPlan: A Framework for Multi-Agent Planning Using Single Agent Planners
Planning problems are, in general, PSPACE-complete; large problems, especially multi-agent problems with required co-ordination, 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, bu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2022-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Subjects: | |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/130647 |
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| Summary: | Planning problems are, in general, PSPACE-complete; large problems, especially multi-agent problems with required co-ordination, 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. |
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| ISSN: | 2334-0754 2334-0762 |