Modifying optimal SAT-based approach to multi-agent path-finding problem to suboptimal variants

Pavel Surynek, Ariel Felner, Roni Stern, Eli Boyarski

Research output: Contribution to conferencePaperpeer-review

6 Scopus citations

Abstract

In multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple agents. Recently, a SAT-based approach was developed to solve this problem and proved beneficial in many cases when compared to other search-based solvers. In this paper, we introduce SAT-based unbounded- and bounded-suboptimal algorithms and compare them to relevant search-based algorithms.

Original languageEnglish
Pages169-170
Number of pages2
StatePublished - 2017
Event10th Annual Symposium on Combinatorial Search, SoCS 2017 - Pittsburgh, United States
Duration: 16 Jun 201717 Jun 2017

Conference

Conference10th Annual Symposium on Combinatorial Search, SoCS 2017
Country/TerritoryUnited States
CityPittsburgh
Period16/06/1717/06/17

Bibliographical note

Publisher Copyright:
Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

This paper is supported by a project commissioned by the New Energy and Industrial Technology Development Organization Japan (NEDO) and the joint grant of the Israel Min- Figure 2: Runtimes of unbounded and bounded algorithms (ϵ = 0.01) on DAO maps brc202d, den520d, and ost003d. This paper is supported by a project commissioned by the New Energy and Industrial Technology Development Organization Japan (NEDO) and the joint grant of the Israel Ministry of Science and the Czech Ministry of Education Youth and Sports number 8G15027. istry of Science and the Czech Ministry of Education Youth and Sports number 8G15027.

FundersFunder number
Czech Ministry of Education Youth and Sports8G15027
Ministerstvo Školství, Mládeže a Tělovýchovy
New Energy and Industrial Technology Development Organization
New Energy and Industrial Technology Development Organization
Ministry of Defense

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