Conflict-Free Multi-Agent Meeting

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

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

2 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 language	English
Title of host publication	31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Editors	Susanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
Publisher	Association for the Advancement of Artificial Intelligence
Pages	16-24
Number of pages	9
ISBN (Electronic)	9781713832317
State	Published - 2021
Externally published	Yes
Event	31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China Duration: 2 Aug 2021 → 13 Aug 2021

Publication series

Name	Proceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume	2021-August
ISSN (Print)	2334-0835
ISSN (Electronic)	2334-0843

Conference

Conference	31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Country/Territory	China
City	Guangzhou, Virtual
Period	2/08/21 → 13/08/21

Bibliographical note

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

Funding

This research was supported by ISF grant 844/17 and BSF grant 2017692 to Ariel Felner.

Funders	Funder number
United States-Israel Binational Science Foundation	2017692
Israel Science Foundation	844/17

Cite this

Atzmon, D., Freiman, S. I., Epshtein, O., Shichman, O., & Felner, A. (2021). Conflict-Free Multi-Agent Meeting. In S. Biundo, M. Do, R. Goldman, M. Katz, Q. Yang, & H. H. Zhuo (Eds.), 31st International Conference on Automated Planning and Scheduling, ICAPS 2021 (pp. 16-24). (Proceedings International Conference on Automated Planning and Scheduling, ICAPS; Vol. 2021-August). Association for the Advancement of Artificial Intelligence.

Atzmon, Dor ; Freiman, Shahar Idan ; Epshtein, Oscar et al. / Conflict-Free Multi-Agent Meeting. 31st International Conference on Automated Planning and Scheduling, ICAPS 2021. editor / Susanne Biundo ; Minh Do ; Robert Goldman ; Michael Katz ; Qiang Yang ; Hankz Hankui Zhuo. Association for the Advancement of Artificial Intelligence, 2021. pp. 16-24 (Proceedings International Conference on Automated Planning and Scheduling, ICAPS).

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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.",

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

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Atzmon, D, Freiman, SI, Epshtein, O, Shichman, O & Felner, A 2021, Conflict-Free Multi-Agent Meeting. in S Biundo, M Do, R Goldman, M Katz, Q Yang & HH Zhuo (eds), 31st International Conference on Automated Planning and Scheduling, ICAPS 2021. Proceedings International Conference on Automated Planning and Scheduling, ICAPS, vol. 2021-August, Association for the Advancement of Artificial Intelligence, pp. 16-24, 31st International Conference on Automated Planning and Scheduling, ICAPS 2021, Guangzhou, Virtual, China, 2/08/21.

Conflict-Free Multi-Agent Meeting. / Atzmon, Dor; Freiman, Shahar Idan; Epshtein, Oscar et al.
31st International Conference on Automated Planning and Scheduling, ICAPS 2021. ed. / Susanne Biundo; Minh Do; Robert Goldman; Michael Katz; Qiang Yang; Hankz Hankui Zhuo. Association for the Advancement of Artificial Intelligence, 2021. p. 16-24 (Proceedings International Conference on Automated Planning and Scheduling, ICAPS; Vol. 2021-August).

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

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AU - Shichman, Oran

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N2 - 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.

AB - 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.

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A2 - Katz, Michael

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PB - Association for the Advancement of Artificial Intelligence

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Atzmon D, Freiman SI, Epshtein O, Shichman O, Felner A. Conflict-Free Multi-Agent Meeting. In Biundo S, Do M, Goldman R, Katz M, Yang Q, Zhuo HH, editors, 31st International Conference on Automated Planning and Scheduling, ICAPS 2021. Association for the Advancement of Artificial Intelligence. 2021. p. 16-24. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS).

Conflict-Free Multi-Agent Meeting

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