@inproceedings{c8dfe66219c54b18b54fdbf93280728c,
title = "Efficient SAT approach to multi-agent path finding under the sum of costs objective",
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.",
author = "Pavel Surynek and Ariel Felner and Roni Stern and Eli Boyarski",
note = "Publisher Copyright: {\textcopyright} 2016 The Authors and IOS Press.; 22nd European Conference on Artificial Intelligence, ECAI 2016 ; Conference date: 29-08-2016 Through 02-09-2016",
year = "2016",
month = jan,
day = "1",
doi = "10.3233/978-1-61499-672-9-810",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "810--818",
editor = "Kaminka, {Gal A.} and Maria Fox and Paolo Bouquet and Eyke Hullermeier and Virginia Dignum and Frank Dignum and {van Harmelen}, Frank",
booktitle = "Frontiers in Artificial Intelligence and Applications",
address = "Netherlands",
}