Efficient SAT Approach to Multi-Agent Path Finding under the Sum of Costs Objective. Surynek, P., Felner, A., Stern, R., & Boyarski, E. In Paper abstract bibtex 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 sumof-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 shown that there are many scenarios where the new SAT-based method outperforms the best variants of previous sum-of-costs search solvers - the ICTS and ICBS algorithms.
@INPROCEEDINGS{dmap2016surynek,
author = {Pavel Surynek and Ariel Felner and Roni Stern and Eli Boyarski},
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 sumof-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 shown that there are many scenarios where the new SAT-based method outperforms the best variants of previous sum-of-costs search solvers - the ICTS and ICBS algorithms.},
url = {https://icaps16.icaps-conference.org/proceedings/dmap16.pdf#page=69}
}
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