Meta-agent conflict-based search for optimal multi-agent path finding

Guni Sharon, Roni Stern, Ariel Felner, Nathan Sturtevant

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

23 Scopus citations


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. It is possible to solve this problem optimally with algorithms that are based on the A* algorithm. Recently, we proposed an alternative algorithm called Conflict-Based Search (CBS) (Sharon et al. 2012), which was shown to outperform the A*-based algorithms in some cases. CBS is a two-level algorithm. At the high level, a search is performed on a tree based on conflicts between agents. At the low level, a search is performed only for a single agent at a time. While in some cases CBS is very efficient, in other cases it is worse than A*-based algorithms. This paper focuses on the latter case by generalizing CBS to Meta-Agent CBS (MA-CBS). The main idea is to couple groups of agents into meta-agents if the number of internal conflicts between them exceeds a given bound. MACBS acts as a framework that can run on top of any complete MAPF solver. We analyze our new approach and provide experimental results demonstrating that it outperforms basic CBS and other A*-based optimal solvers in many cases.

Original languageEnglish
Title of host publicationProceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012
Number of pages8
StatePublished - 1 Dec 2012
Event5th International Symposium on Combinatorial Search, SoCS 2012 - Niagara Falls, ON, Canada
Duration: 19 Jul 201221 Jul 2012

Publication series

NameProceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012


Conference5th International Symposium on Combinatorial Search, SoCS 2012
CityNiagara Falls, ON

ASJC Scopus subject areas

  • Computer Networks and Communications

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