OTHER
Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios
Hang Ma, Sven Koenig, Nora Ayanian, Liron Cohen, Wolfgang Hoenig, T. K. Satish Kumar, Tansel Uras, Hong Xu, Craig Tovey, Guni Sharon
- Year
- 2017
- Access
- Open access
Abstract
Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when generalizing MAPF methods to real-world scenarios and four research directions that address them. We emphasize the importance of addressing these issues as opposed to developing faster methods for the standard formulation of the MAPF problem.
Keywords
cs.AIcs.MAcs.RO
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
OTHER
Open access📊 20,501 cites
Fractional Differential Equations
Igor Podlubný
2025
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
OTHER
📊 13,277 cites
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992