Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges
Felner, Ariel (Ben-Gurion University of the Negev) | Stern, Roni (Ben-Gurion University of the Negev) | Shimony, Solomon Eyal (Ben-Gurion University of the Negev) | Boyarski, Eli (Bar-Ilan University) | Goldenberg, Meir (The Jerusalem College of Technology) | Sharon, Guni (The University of Texas at Austin) | Sturtevant, Nathan (The University of Denver) | Wagner, Glenn (Carnegie Mellon University) | Surynek, Pavel (National Institute of Advanced Industrial Science and Technology)
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.
- Country:
- North America > United States
- Texas (0.04)
- Asia
- Middle East > Israel
- Jerusalem District > Jerusalem (0.04)
- Japan > Honshū
- Kantō > Tokyo Metropolis Prefecture > Tokyo (0.14)
- Middle East > Israel
- North America > United States
- Genre:
- Research Report (0.46)
- Overview (0.46)
- Technology: