Experimental Evaluation of Classical Multi Agent Path Finding Algorithms

Omri Kaduri, Eli Boyarski, Roni Stern

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

4 Scopus citations

Abstract

Modern optimal multi-agent path finding (MAPF) algorithms can scale to solve problems with hundreds of agents. To facilitate comparison between these algorithms, a benchmark of MAPF problems was recently proposed. We report a comprehensive evaluation of a diverse set of state-of-the-art optimal MAPF algorithms over the entire benchmark. The results show that in terms of coverage, the recently proposed Lazy CBS algorithm outperforms all others significantly, but it is usually not the fastest algorithm. This suggests algorithm selection methods can be beneficial. Then, we characterize different setups for algorithm selection in MAPF, and evaluate simple baselines for each setup. Finally, we propose an extension of the existing MAPF benchmark in the form of different ways to distribute the agents’ source and target locations.

Original languageEnglish
Title of host publication14th International Symposium on Combinatorial Search, SoCS 2021
EditorsHang Ma, Ivan Serina
PublisherAssociation for the Advancement of Artificial Intelligence
Pages126-130
Number of pages5
ISBN (Electronic)9781713834557
StatePublished - 1 Jan 2021
Event14th International Symposium on Combinatorial Search, SoCS 2021 - Guangzhou, Virtual, China
Duration: 26 Jul 202130 Jul 2021

Publication series

Name14th International Symposium on Combinatorial Search, SoCS 2021

Conference

Conference14th International Symposium on Combinatorial Search, SoCS 2021
Country/TerritoryChina
CityGuangzhou, Virtual
Period26/07/2130/07/21

ASJC Scopus subject areas

  • Computer Networks and Communications

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