Sub-optimal SAT-based approach to multi-agent path-finding problem

Pavel Surynek; Ariel Felner; Roni Stern; Eli Boyarski

Sub-optimal SAT-based approach to multi-agent path-finding problem

Pavel Surynek, Ariel Felner, Roni Stern, Eli Boyarski

Department of Computer Science

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

7 Scopus citations

Abstract

In multi-agent path finding (MAPF) the task is to find nonconflicting paths for multiple agents. In this paper we focus on finding suboptimal solutions for MAPF for the sumof- costs variant. Recently, a SAT-based approached was developed to solve this problem and proved beneficial in many cases when compared to other search-based solvers. In this paper, we present SAT-based unbounded- and boundedsuboptimal algorithms and compare them to relevant algorithms. Experimental results show that in many case the SAT-based solver significantly outperforms the search-based solvers.

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	99-105
Number of pages	7
ISBN (Electronic)	9781577358022
State	Published - 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

Bibliographical note

Publisher Copyright:
© 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Cite this

@inproceedings{599d8a5d0e984964b2f6b1b8ba662aeb,

title = "Sub-optimal SAT-based approach to multi-agent path-finding problem",

abstract = "In multi-agent path finding (MAPF) the task is to find nonconflicting paths for multiple agents. In this paper we focus on finding suboptimal solutions for MAPF for the sumof- costs variant. Recently, a SAT-based approached was developed to solve this problem and proved beneficial in many cases when compared to other search-based solvers. In this paper, we present SAT-based unbounded- and boundedsuboptimal algorithms and compare them to relevant algorithms. Experimental results show that in many case the SAT-based solver significantly outperforms the search-based solvers.",

author = "Pavel Surynek and Ariel Felner and Roni Stern and Eli Boyarski",

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",

language = "אנגלית",

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

publisher = "AAAI press",

pages = "99--105",

editor = "Vadim Bulitko and Sabine Storandt",

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

}

Surynek, P, Felner, A, Stern, R & Boyarski, E 2018, Sub-optimal SAT-based approach to multi-agent path-finding problem. 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. 99-105, 11th International Symposium on Combinatorial Search, SoCS 2018, Stockholm, Sweden, 14/07/18.

Sub-optimal SAT-based approach to multi-agent path-finding problem. / Surynek, Pavel; Felner, Ariel; Stern, Roni et al.
Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018. ed. / Vadim Bulitko; Sabine Storandt. AAAI press, 2018. p. 99-105 (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 - Sub-optimal SAT-based approach to multi-agent path-finding problem

AU - Surynek, Pavel

AU - Felner, Ariel

AU - Stern, Roni

AU - Boyarski, Eli

PY - 2018

Y1 - 2018

N2 - In multi-agent path finding (MAPF) the task is to find nonconflicting paths for multiple agents. In this paper we focus on finding suboptimal solutions for MAPF for the sumof- costs variant. Recently, a SAT-based approached was developed to solve this problem and proved beneficial in many cases when compared to other search-based solvers. In this paper, we present SAT-based unbounded- and boundedsuboptimal algorithms and compare them to relevant algorithms. Experimental results show that in many case the SAT-based solver significantly outperforms the search-based solvers.

AB - In multi-agent path finding (MAPF) the task is to find nonconflicting paths for multiple agents. In this paper we focus on finding suboptimal solutions for MAPF for the sumof- costs variant. Recently, a SAT-based approached was developed to solve this problem and proved beneficial in many cases when compared to other search-based solvers. In this paper, we present SAT-based unbounded- and boundedsuboptimal algorithms and compare them to relevant algorithms. Experimental results show that in many case the SAT-based solver significantly outperforms the search-based solvers.

UR - http://www.scopus.com/inward/record.url?scp=85091035103&partnerID=8YFLogxK

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85091035103

T3 - Proceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018

SP - 99

EP - 105

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

A2 - Bulitko, Vadim

A2 - Storandt, Sabine

PB - AAAI press

T2 - 11th International Symposium on Combinatorial Search, SoCS 2018

Y2 - 14 July 2018 through 15 July 2018

ER -

Sub-optimal SAT-based approach to multi-agent path-finding problem

Abstract

Publication series

Conference

Bibliographical note

Other files and links

Fingerprint

Cite this