Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios
Hang Ma, Sven Koenig, Nora Ayanian, Liron Cohen, Hoenig, Wolfgang, T. K. Satish Kumar, Tansel Uras, Hong Xu, Craig A. Tovey, Guni Sharon · arXiv (Cornell University) · 2017
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.