Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges
- Ariel Felner, Information Systems Engineering, Ben-Gurion University, Israel
- Roni Stern
- Solomon Eyal Shimony
- Eli Boyarski
- Meir Goldenberg
- Guni Sharon
- Nathan R. Sturtevant
- Glenn Wagner
- Pavel Surynek
Multi-agent pathfinding (MAPF) is an area of expanding research interest. At the core of this research area, numerous diverse search-based techniques were developed in the past 6 years for optimally solving MAPF under the sum-of-costs objective function. In this paper we survey these techniques, while placing them into the wider context of the MAPF field of research. Finally, we provide analytical and experimental comparisons that show that no algorithm dominates all others in all circumstances. We conclude by listing important future research directions.
Citation
A. Felner, R. Stern, S. Shimony, E. Boyarski, M. Goldenberg, G. Sharon, N. Sturtevant, G. Wagner, P. Surynek. "Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges". Symposium on Combinatorial Search, (ed: Alex Fukunaga, Akihiro Kishimoto), pp 29-37, June 2017.| Keywords: | |
| Category: | In Conference |
| Web Links: | AAAI |
BibTeX
@incollection{Felner+al:SoCS17,
author = {Ariel Felner and Roni Stern and Solomon Eyal Shimony and Eli
Boyarski and Meir Goldenberg and Guni Sharon and Nathan R. Sturtevant and
Glenn Wagner and Pavel Surynek},
title = {Search-Based Optimal Solvers for the Multi-Agent Pathfinding
Problem: Summary and Challenges},
Editor = {Alex Fukunaga, Akihiro Kishimoto},
Pages = {29-37},
booktitle = {Symposium on Combinatorial Search},
year = 2017,
}Last Updated: July 05, 2020Submitted by Sabina P
