Generalizing multi-agent path finding for heterogeneous agents

Dor Atzmon, Yonathan Zax, Einat Kivity, Lidor Avitan, Jonathan Morag, Ariel Felner

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

5 Scopus citations

Abstract

Multi-Agent Path Finding (MAPF) is the problem of finding non-colliding paths for multiple agents. The classical problem assumes that all agents are homogeneous, with a fixed size and behavior. However, in reality agents are heterogeneous. In this paper, we generalize MAPF to the case of general, heterogeneous agents (G-MAPF). We then show how two previous settings of large agents and k-robust agents are special cases of G-MAPF. Finally, we introduce G-CBS, a variant of the Conflict-Based Search (CBS) algorithm for GMAPF, which does not cause significant extra overhead.

Original languageEnglish
Title of host publicationProceedings of the 13th International Symposium on Combinatorial Search, SoCS 2020
EditorsDaniel Harabor, Mauro Vallati
PublisherThe AAAI Press
Pages101-105
Number of pages5
ISBN (Electronic)9781577358220
StatePublished - 2020
Externally publishedYes
Event13th International Symposium on Combinatorial Search, SoCS 2020 - Virtual, Online
Duration: 26 May 202028 May 2020

Publication series

NameProceedings of the 13th International Symposium on Combinatorial Search, SoCS 2020

Conference

Conference13th International Symposium on Combinatorial Search, SoCS 2020
CityVirtual, Online
Period26/05/2028/05/20

Bibliographical note

Publisher Copyright:
© 2020 Proceedings of the 13th International Symposium on Combinatorial Search, SoCS 2020. All rights reserved.

Fingerprint

Dive into the research topics of 'Generalizing multi-agent path finding for heterogeneous agents'. Together they form a unique fingerprint.

Cite this