Conflict-Free Multi-Agent Meeting

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

doi:10.1609/socs.v12i1.18565

Conflict-Free Multi-Agent Meeting

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

Ben-Gurion University of the Negev

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Multi-Agent Meeting (MAM) is the problem of finding a meeting location for multiple agents and paths to that location. Recently, a Multi-Directional Heuristic Search algorithm, called MM*, was introduced. MM* is a state-of-the-art MAM optimal solver that searches from multiple directions (one for each agent) and is guided by a heuristic function. 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 compare both algorithms experimentally, showing the pros and cons of each algorithm.

Original language	English
Title of host publication	14th International Symposium on Combinatorial Search, SoCS 2021
Editors	Hang Ma, Ivan Serina
Publisher	Association for the Advancement of Artificial Intelligence
Pages	147-149
Number of pages	3
ISBN (Electronic)	9781713834557
DOIs	https://doi.org/10.1609/socs.v12i1.18565
State	Published - 2021
Externally published	Yes
Event	14th International Symposium on Combinatorial Search, SoCS 2021 - Guangzhou, Virtual, China Duration: 26 Jul 2021 → 30 Jul 2021

Publication series

Name	14th International Symposium on Combinatorial Search, SoCS 2021

Conference

Conference	14th International Symposium on Combinatorial Search, SoCS 2021
Country/Territory	China
City	Guangzhou, Virtual
Period	26/07/21 → 30/07/21

Bibliographical note

Publisher Copyright:
Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Access to Document

10.1609/socs.v12i1.18565

Cite this

Atzmon, D., Freiman, S. I., Epshtein, O., Shichman, O., & Felner, A. (2021). Conflict-Free Multi-Agent Meeting. In H. Ma, & I. Serina (Eds.), 14th International Symposium on Combinatorial Search, SoCS 2021 (pp. 147-149). (14th International Symposium on Combinatorial Search, SoCS 2021). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/socs.v12i1.18565

@inproceedings{1bc1e1239c1c4b0fbcf51b10fbd90ac7,

title = "Conflict-Free Multi-Agent Meeting",

abstract = "Multi-Agent Meeting (MAM) is the problem of finding a meeting location for multiple agents and paths to that location. Recently, a Multi-Directional Heuristic Search algorithm, called MM*, was introduced. MM* is a state-of-the-art MAM optimal solver that searches from multiple directions (one for each agent) and is guided by a heuristic function. 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 compare both algorithms experimentally, showing the pros and cons of each algorithm.",

author = "Dor Atzmon and Freiman, \{Shahar Idan\} and Oscar Epshtein and Oran Shichman and Ariel Felner",

note = "Publisher Copyright: Copyright {\textcopyright} 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 14th International Symposium on Combinatorial Search, SoCS 2021 ; Conference date: 26-07-2021 Through 30-07-2021",

year = "2021",

doi = "10.1609/socs.v12i1.18565",

language = "אנגלית",

series = "14th International Symposium on Combinatorial Search, SoCS 2021",

publisher = "Association for the Advancement of Artificial Intelligence",

pages = "147--149",

editor = "Hang Ma and Ivan Serina",

booktitle = "14th International Symposium on Combinatorial Search, SoCS 2021",

}

Atzmon, D, Freiman, SI, Epshtein, O, Shichman, O & Felner, A 2021, Conflict-Free Multi-Agent Meeting. in H Ma & I Serina (eds), 14th International Symposium on Combinatorial Search, SoCS 2021. 14th International Symposium on Combinatorial Search, SoCS 2021, Association for the Advancement of Artificial Intelligence, pp. 147-149, 14th International Symposium on Combinatorial Search, SoCS 2021, Guangzhou, Virtual, China, 26/07/21. https://doi.org/10.1609/socs.v12i1.18565

Conflict-Free Multi-Agent Meeting. / Atzmon, Dor; Freiman, Shahar Idan; Epshtein, Oscar et al.
14th International Symposium on Combinatorial Search, SoCS 2021. ed. / Hang Ma; Ivan Serina. Association for the Advancement of Artificial Intelligence, 2021. p. 147-149 (14th International Symposium on Combinatorial Search, SoCS 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shichman, Oran

AU - Felner, Ariel

PY - 2021

Y1 - 2021

N2 - Multi-Agent Meeting (MAM) is the problem of finding a meeting location for multiple agents and paths to that location. Recently, a Multi-Directional Heuristic Search algorithm, called MM*, was introduced. MM* is a state-of-the-art MAM optimal solver that searches from multiple directions (one for each agent) and is guided by a heuristic function. 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 compare both algorithms experimentally, showing the pros and cons of each algorithm.

AB - Multi-Agent Meeting (MAM) is the problem of finding a meeting location for multiple agents and paths to that location. Recently, a Multi-Directional Heuristic Search algorithm, called MM*, was introduced. MM* is a state-of-the-art MAM optimal solver that searches from multiple directions (one for each agent) and is guided by a heuristic function. 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 compare both algorithms experimentally, showing the pros and cons of each algorithm.

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ER -

Conflict-Free Multi-Agent Meeting

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