Efficient SAT approach to multi-agent path finding under the sum of costs objective

Pavel Surynek, Ariel Felner, Roni Stern, Eli Boyarski

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

83 Scopus citations

Abstract

In the multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple agents. In this paper we present the first SAT-solver for the sum-of-costs variant of MAPF which was previously only solved by search-based methods. Using both a lower bound on the sum-of-costs and an upper bound on the makespan, we are able to have a reasonable number of variables in our SAT encoding. We then further improve the encoding by borrowing ideas from ICTS, a search-based solver. Experimental evaluation on several domains showed that there are many scenarios where the new SAT-based method outperforms the best variants of previous sumof-costs search solvers - the ICTS and ICBS algorithms.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
EditorsGal A. Kaminka, Frank Dignum, Eyke Hullermeier, Paolo Bouquet, Virginia Dignum, Maria Fox, Frank van Harmelen
PublisherIOS Press
Pages810-818
Number of pages9
ISBN (Electronic)9781614996712
DOIs
StatePublished - 1 Jan 2016
Event22nd European Conference on Artificial Intelligence, ECAI 2016 - The Hague, Netherlands
Duration: 29 Aug 20162 Sep 2016

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume285
ISSN (Print)0922-6389

Conference

Conference22nd European Conference on Artificial Intelligence, ECAI 2016
Country/TerritoryNetherlands
CityThe Hague
Period29/08/162/09/16

ASJC Scopus subject areas

  • Artificial Intelligence

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