Suboptimal variants of the conflict-based search algorithm for the multi-agent pathfinding problem

Max Barer, Guni Sharon, Ron Zvi Stern, Ariel Felner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

98 Scopus citations

Abstract

The task in the multi-agent path finding problem (MAPF) is to find paths for multiple agents, each with a different start and goal position, such that agents do not collide. A successful optimal MAPF solver is the conflict-based search (CBS) algorithm. CBS is a two level algorithm where special conditions ensure it returns the optimal solution. Solving MAPF optimally is proven to be NP-hard, hence CBS and all other optimal solvers do not scale up. We propose several ways to relax the optimality conditions of CBS trading solution quality for runtime as well as bounded-suboptimal variants, where the returned solution is guaranteed to be within a constant factor from optimal solution cost. Experimental results show the benefits of our new approach; a massive reduction in running time is presented while sacrificing a minor loss in solution quality. Our new algorithms outperform other existing algorithms in most of the cases.

Original languageEnglish
Title of host publicationProceedings of the 7th Annual Symposium on Combinatorial Search, SoCS 2014
EditorsStefan Edelkamp, Roman Bartak
PublisherAAAI press
Pages19-27
Number of pages9
ISBN (Electronic)9781577356769
StatePublished - 1 Jan 2014
Externally publishedYes
Event7th Annual Symposium on Combinatorial Search, SoCS 2014 - Prague, Czech Republic
Duration: 15 Aug 201417 Aug 2014

Publication series

NameProceedings of the 7th Annual Symposium on Combinatorial Search, SoCS 2014
Volume2014-January

Conference

Conference7th Annual Symposium on Combinatorial Search, SoCS 2014
Country/TerritoryCzech Republic
CityPrague
Period15/08/1417/08/14

ASJC Scopus subject areas

  • Computer Networks and Communications

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