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

Pavel Surynek; Ariel Felner; Roni Stern; Eli Boyarski

doi:10.3233/978-1-61499-672-9-810

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

Pavel Surynek, Ariel Felner, Roni Stern, Eli Boyarski

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

118 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 language	English
Title of host publication	Frontiers in Artificial Intelligence and Applications
Editors	Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hullermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen
Publisher	IOS Press BV
Pages	810-818
Number of pages	9
ISBN (Electronic)	9781614996712
DOIs	https://doi.org/10.3233/978-1-61499-672-9-810
State	Published - 2016
Event	22nd European Conference on Artificial Intelligence, ECAI 2016 - The Hague, Netherlands Duration: 29 Aug 2016 → 2 Sep 2016

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	285
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	22nd European Conference on Artificial Intelligence, ECAI 2016
Country/Territory	Netherlands
City	The Hague
Period	29/08/16 → 2/09/16

Bibliographical note

Publisher Copyright:
© 2016 The Authors and IOS Press.

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10.3233/978-1-61499-672-9-810

Cite this

Surynek, P., Felner, A., Stern, R., & Boyarski, E. (2016). Efficient SAT approach to multi-agent path finding under the sum of costs objective. In G. A. Kaminka, M. Fox, P. Bouquet, E. Hullermeier, V. Dignum, F. Dignum, & F. van Harmelen (Eds.), Frontiers in Artificial Intelligence and Applications (pp. 810-818). (Frontiers in Artificial Intelligence and Applications; Vol. 285). IOS Press BV. https://doi.org/10.3233/978-1-61499-672-9-810

Surynek, Pavel ; Felner, Ariel ; Stern, Roni et al. / Efficient SAT approach to multi-agent path finding under the sum of costs objective. Frontiers in Artificial Intelligence and Applications. editor / Gal A. Kaminka ; Maria Fox ; Paolo Bouquet ; Eyke Hullermeier ; Virginia Dignum ; Frank Dignum ; Frank van Harmelen. IOS Press BV, 2016. pp. 810-818 (Frontiers in Artificial Intelligence and Applications).

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Surynek, P, Felner, A, Stern, R & Boyarski, E 2016, Efficient SAT approach to multi-agent path finding under the sum of costs objective. in GA Kaminka, M Fox, P Bouquet, E Hullermeier, V Dignum, F Dignum & F van Harmelen (eds), Frontiers in Artificial Intelligence and Applications. Frontiers in Artificial Intelligence and Applications, vol. 285, IOS Press BV, pp. 810-818, 22nd European Conference on Artificial Intelligence, ECAI 2016, The Hague, Netherlands, 29/08/16. https://doi.org/10.3233/978-1-61499-672-9-810

Efficient SAT approach to multi-agent path finding under the sum of costs objective. / Surynek, Pavel; Felner, Ariel; Stern, Roni et al.
Frontiers in Artificial Intelligence and Applications. ed. / Gal A. Kaminka; Maria Fox; Paolo Bouquet; Eyke Hullermeier; Virginia Dignum; Frank Dignum; Frank van Harmelen. IOS Press BV, 2016. p. 810-818 (Frontiers in Artificial Intelligence and Applications; Vol. 285).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Surynek P, Felner A, Stern R, Boyarski E. Efficient SAT approach to multi-agent path finding under the sum of costs objective. In Kaminka GA, Fox M, Bouquet P, Hullermeier E, Dignum V, Dignum F, van Harmelen F, editors, Frontiers in Artificial Intelligence and Applications. IOS Press BV. 2016. p. 810-818. (Frontiers in Artificial Intelligence and Applications). doi: 10.3233/978-1-61499-672-9-810

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

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