Boolean satisfiability approach to optimal 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

5 Scopus citations

Abstract

This paper focuses on finding optimal solutions to the multiagent path finding (MAPF) problem over undirected graphs where the task is to find non-colliding paths for multiple agents, each with a different start and goal position. An encoding of MAPF to Boolean satisfiability (SAT) is already known to the makespan optimal variant of the problem. In this paper we present the first SAT-solver for minimizing the sum of costs enabled by introducing cardinality constraints into the SAT encoding. An experimental evaluation on grid graphs indicate promising performance of the new SAT-based method in comparison with the best variants of previous sum-of-costs search solvers.

Original languageEnglish
Title of host publicationAAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1435-1436
Number of pages2
ISBN (Electronic)9781450342391
StatePublished - 1 Jan 2016
Event15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore
Duration: 9 May 201613 May 2016

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
Country/TerritorySingapore
CitySingapore
Period9/05/1613/05/16

Keywords

  • Boolean satisfiability (SAT)
  • Makespan objective
  • Multi-agent path finding (MAPF)
  • Sum of costs objective

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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