Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges. Felner, A., Stern, R., Shimony, E., Goldenberg, M., Sharon, G., Sturtevant, N., Wagner, G., & Surynek, P. In Proceedings of the Symposium on Combinatorial Search (SoCS), pages 28–37, 2017.
abstract   bibtex   
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.
@INPROCEEDINGS{AFeln17c, 
 AUTHOR= "A. Felner and R. Stern and E. Shimony and M. Goldenberg and G. Sharon and N. Sturtevant and G. Wagner and P. Surynek",
 TITLE= "Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges",
 BOOKTITLE= "Proceedings of the Symposium on Combinatorial Search (SoCS)",
 PAGES= "28--37",
 YEAR= "2017",
 PDF= "https://docs.wixstatic.com/ugd/749b4b_e9f4afe500e14e09b02699b8237fc7bb.pdf",
 FLAGS= ":2017:,:arielfelner:,:ronistern:,:nathansturtevant:,:gunisharon:,:pavelsurynek:,:glennwagner:",
 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."
}

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