Online multi-agent pathfinding

Jirí Švancara; Marek Vlk; Roni Stern; Dor Atzmon; Roman Barták

Online multi-agent pathfinding

Jirí Švancara, Marek Vlk, Roni Stern, Dor Atzmon, Roman Barták

Department of Software and Information Systems Engineering

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

52 Scopus citations

Abstract

Multi-agent pathfinding (MAPF) is the problem of moving a group of agents to a set of target destinations while avoiding collisions. In this work, we study the online version of MAPF where new agents appear over time. Several variants of online MAPF are defined and analyzed theoretically, showing that it is not possible to create an optimal online MAPF solver. Nevertheless, we propose effective online MAPF algorithms that balance solution quality, runtime, and the number of plan changes an agent makes during execution.

Original language	English
Title of host publication	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Publisher	AAAI press
Pages	7732-7739
Number of pages	8
ISBN (Electronic)	9781577358091
State	Published - 1 Jan 2019
Event	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 - Honolulu, United States Duration: 27 Jan 2019 → 1 Feb 2019

Publication series

Name	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

Conference

Conference	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Country/Territory	United States
City	Honolulu
Period	27/01/19 → 1/02/19

ASJC Scopus subject areas

Artificial Intelligence

Cite this

Švancara, J., Vlk, M., Stern, R., Atzmon, D., & Barták, R. (2019). Online multi-agent pathfinding. In 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 (pp. 7732-7739). (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019). AAAI press.

Švancara, Jirí ; Vlk, Marek ; Stern, Roni et al. / Online multi-agent pathfinding. 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press, 2019. pp. 7732-7739 (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019).

@inproceedings{7c678a9bfe674131bdb81c1b3ace9c8e,

title = "Online multi-agent pathfinding",

abstract = "Multi-agent pathfinding (MAPF) is the problem of moving a group of agents to a set of target destinations while avoiding collisions. In this work, we study the online version of MAPF where new agents appear over time. Several variants of online MAPF are defined and analyzed theoretically, showing that it is not possible to create an optimal online MAPF solver. Nevertheless, we propose effective online MAPF algorithms that balance solution quality, runtime, and the number of plan changes an agent makes during execution.",

author = "Jir{\'i} {\v S}vancara and Marek Vlk and Roni Stern and Dor Atzmon and Roman Bart{\'a}k",

note = "Publisher Copyright: {\textcopyright} 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 ; Conference date: 27-01-2019 Through 01-02-2019",

year = "2019",

month = jan,

day = "1",

language = "English",

series = "33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019",

publisher = "AAAI press",

pages = "7732--7739",

booktitle = "33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019",

}

Švancara, J, Vlk, M, Stern, R, Atzmon, D & Barták, R 2019, Online multi-agent pathfinding. in 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, AAAI press, pp. 7732-7739, 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, United States, 27/01/19.

Online multi-agent pathfinding. / Švancara, Jirí; Vlk, Marek; Stern, Roni et al.
33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press, 2019. p. 7732-7739 (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019).

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

TY - GEN

T1 - Online multi-agent pathfinding

AU - Švancara, Jirí

AU - Vlk, Marek

AU - Stern, Roni

AU - Atzmon, Dor

AU - Barták, Roman

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Multi-agent pathfinding (MAPF) is the problem of moving a group of agents to a set of target destinations while avoiding collisions. In this work, we study the online version of MAPF where new agents appear over time. Several variants of online MAPF are defined and analyzed theoretically, showing that it is not possible to create an optimal online MAPF solver. Nevertheless, we propose effective online MAPF algorithms that balance solution quality, runtime, and the number of plan changes an agent makes during execution.

AB - Multi-agent pathfinding (MAPF) is the problem of moving a group of agents to a set of target destinations while avoiding collisions. In this work, we study the online version of MAPF where new agents appear over time. Several variants of online MAPF are defined and analyzed theoretically, showing that it is not possible to create an optimal online MAPF solver. Nevertheless, we propose effective online MAPF algorithms that balance solution quality, runtime, and the number of plan changes an agent makes during execution.

UR - http://www.scopus.com/inward/record.url?scp=85076102091&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85076102091

T3 - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

SP - 7732

EP - 7739

BT - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

PB - AAAI press

T2 - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

Y2 - 27 January 2019 through 1 February 2019

ER -

Švancara J, Vlk M, Stern R, Atzmon D, Barták R. Online multi-agent pathfinding. In 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press. 2019. p. 7732-7739. (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019).

Online multi-agent pathfinding

Abstract

Publication series

Conference

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this