Robust Multi-agent path finding

Dor Atzmon; Roni Stern; Ariel Felner; Glenn Wagner; Roman Bartak; Neng Fa Zhou

Robust Multi-agent path finding

Dor Atzmon, Roni Stern, Ariel Felner, Glenn Wagner, Roman Bartak, Neng Fa Zhou

Department of Software and Information Systems Engineering

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

30 Scopus citations

Abstract

In the multi-agent path-finding (MAPF) problem, the task is to find a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. We explore the notion of k- robust MAPF, where the task is to find a plan that can be followed even if a limited number of such delays occur. k- robust MAPF is especially suitable for agents with a control mechanism that guarantees that each agent is within a limited number of steps away from its pre-defined plan. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we show the benefit of using a k-robust plan during execution, and for finding plans that are likely to succeed.

Original language	English
Title of host publication	Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018
Editors	Vadim Bulitko, Sabine Storandt
Publisher	AAAI press
Pages	2-9
Number of pages	8
ISBN (Electronic)	9781577358022
State	Published - 1 Jan 2018
Event	11th International Symposium on Combinatorial Search, SoCS 2018 - Stockholm, Sweden Duration: 14 Jul 2018 → 15 Jul 2018

Publication series

Name	Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018

Conference

Conference	11th International Symposium on Combinatorial Search, SoCS 2018
Country/Territory	Sweden
City	Stockholm
Period	14/07/18 → 15/07/18

ASJC Scopus subject areas

Computer Networks and Communications

Cite this

@inproceedings{b955d32879894b4aad37e928eb232807,

title = "Robust Multi-agent path finding",

abstract = "In the multi-agent path-finding (MAPF) problem, the task is to find a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. We explore the notion of k- robust MAPF, where the task is to find a plan that can be followed even if a limited number of such delays occur. k- robust MAPF is especially suitable for agents with a control mechanism that guarantees that each agent is within a limited number of steps away from its pre-defined plan. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we show the benefit of using a k-robust plan during execution, and for finding plans that are likely to succeed.",

author = "Dor Atzmon and Roni Stern and Ariel Felner and Glenn Wagner and Roman Bartak and Zhou, {Neng Fa}",

note = "Publisher Copyright: {\textcopyright} 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 11th International Symposium on Combinatorial Search, SoCS 2018 ; Conference date: 14-07-2018 Through 15-07-2018",

year = "2018",

month = jan,

day = "1",

language = "English",

series = "Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018",

publisher = "AAAI press",

pages = "2--9",

editor = "Vadim Bulitko and Sabine Storandt",

booktitle = "Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018",

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Atzmon, D, Stern, R , Felner, A, Wagner, G, Bartak, R & Zhou, NF 2018, Robust Multi-agent path finding. in V Bulitko & S Storandt (eds), Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018. Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018, AAAI press, pp. 2-9, 11th International Symposium on Combinatorial Search, SoCS 2018, Stockholm, Sweden, 14/07/18.

Robust Multi-agent path finding. / Atzmon, Dor; Stern, Roni ; Felner, Ariel et al.
Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018. ed. / Vadim Bulitko; Sabine Storandt. AAAI press, 2018. p. 2-9 (Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018).

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

TY - GEN

T1 - Robust Multi-agent path finding

AU - Atzmon, Dor

AU - Stern, Roni

AU - Felner, Ariel

AU - Wagner, Glenn

AU - Bartak, Roman

AU - Zhou, Neng Fa

PY - 2018/1/1

Y1 - 2018/1/1

N2 - In the multi-agent path-finding (MAPF) problem, the task is to find a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. We explore the notion of k- robust MAPF, where the task is to find a plan that can be followed even if a limited number of such delays occur. k- robust MAPF is especially suitable for agents with a control mechanism that guarantees that each agent is within a limited number of steps away from its pre-defined plan. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we show the benefit of using a k-robust plan during execution, and for finding plans that are likely to succeed.

AB - In the multi-agent path-finding (MAPF) problem, the task is to find a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. We explore the notion of k- robust MAPF, where the task is to find a plan that can be followed even if a limited number of such delays occur. k- robust MAPF is especially suitable for agents with a control mechanism that guarantees that each agent is within a limited number of steps away from its pre-defined plan. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we show the benefit of using a k-robust plan during execution, and for finding plans that are likely to succeed.

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M3 - Conference contribution

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BT - Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018

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Robust Multi-agent path finding

Abstract

Publication series

Conference

ASJC Scopus subject areas

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