Solving concurrent multiagent planning using classical planning

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To access the full text documents, please follow this link: http://hdl.handle.net/10230/34741

dc.contributor.author	Furelos Blanco, Daniel
dc.contributor.author	Jonsson, Anders, 1973-
dc.date	2018
dc.identifier.citation	Furelos-Blanco D, Jonsson A. Solving concurrent multiagent planning using classical planning. In: Stolba M, Komenda A, editors. DMAP 2018. Proceedings of the 6th Workshop on Distributed and Multi-Agent Planning; 2018 Jun 24-29; Delft, the Netherlands. Palo Alto (CA): AAAI; 2018. p. 8-16.
dc.identifier.uri	http://hdl.handle.net/10230/34741
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	Association for the Advancement of Artificial Intelligence (AAAI) - Congrés ICAPS17
dc.relation	Stolba M, Komenda A, editors. DMAP 2018. Proceedings of the 6th Workshop on Distributed and Multi-Agent Planning; 2018 Jun 24-29; Delft, the Netherlands. Palo Alto (CA): AAAI; 2018. p. 8-16.
dc.rights	Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Planificació -- Automatització
dc.title	Solving concurrent multiagent planning using classical planning
dc.type	info:eu-repo/semantics/conferenceObject
dc.type	info:eu-repo/semantics/publishedVersion
dc.description.abstract	Comunicació presentada al 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018), celebrat durant la 28th International Conference on Automated Planning and Scheduling, els dies 24 a 29 de juny de 2018 a Delft, Països Baixos.
dc.description.abstract	In this work we present a novel approach to solving concurrent multiagent planning problems in which several agents act in parallel. Our approach relies on a compilation from concurrent multiagent planning to classical planning, allowing us to use an off-the-shelf classical planner to solve the original multiagent problem. The solution can be directly interpreted as a concurrent plan that satisfies a given set of concurrency constraints, while avoiding the exponential blowup associated with concurrent actions. Theoretically, we show that the compilation is sound and complete. Empirically, we show that our compilation can solve challenging multiagent planning problems that require concurrent actions.
dc.description.abstract	This work has been supported by the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).

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