Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges Conference Paper

abstract

• 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.

authors

• Sharon, Guni

published proceedings

• Proceedings of the International Symposium on Combinatorial Search

author list (cited authors)

• Felner, A., Stern, R., Shimony, S., Boyarski, E., Goldenberg, M., Sharon, G., ... Surynek, P.

citation count

• 35

complete list of authors

• Felner, Ariel||Stern, Roni||Shimony, Solomon||Boyarski, Eli||Goldenberg, Meir||Sharon, Guni||Sturtevant, Nathan||Wagner, Glenn||Surynek, Pavel

publication date

• January 2017

publisher

• Association for the Advancement of Artificial Intelligence (AAAI)  Publisher

published in

• n2832-9171ISSN  Journal

keywords

• 46 Information And Computing Sciences
• 4602 Artificial Intelligence

Digital Object Identifier (DOI)

• 10.1609/socs.v8i1.18423

start page

• 29

end page

• 37

volume

• 8

issue

• 1

URL

• http://dx.doi.org/10.1609/socs.v8i1.18423