Conflict-Free Multi-Agent Meeting

Dor Atzmon, Shahar Idan Freiman, Oscar Epshtein, Oran Shichman, Ariel Felner

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

1 Scopus citations

Abstract

Multi-Agent Meeting (MAM) is the problem of finding a meeting location for multiple agents and paths to that location. Practically, a solution to MAM may contain conflicting paths. A related problem that plans conflict-free paths to a given set of goal locations is the Multi-Agent Path Finding problem (MAPF). In this paper, we solve the Conflict-Free Multi-Agent Meeting problem (CF-MAM). In CF-MAM, we find a meeting location for multiple agents (as in MAM) as well as conflict-free paths (as in MAPF) to that location. We introduce two novel algorithms, which combine MAM and MAPF solvers, for optimally solving CF-MAM. We prove the optimality of both algorithms and compare them experimentally, showing the pros and cons of each algorithm.

Original languageEnglish
Title of host publication31st International Conference on Automated Planning and Scheduling, ICAPS 2021
EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
PublisherAssociation for the Advancement of Artificial Intelligence
Pages16-24
Number of pages9
ISBN (Electronic)9781713832317
StatePublished - 1 Jan 2021
Event31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China
Duration: 2 Aug 202113 Aug 2021

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2021-August
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Country/TerritoryChina
CityGuangzhou, Virtual
Period2/08/2113/08/21

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management

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