AbstractH. Ma, S. Koenig, N. Ayanian, L. Cohen, W. Hoenig, S. Kumar, T. Uras, H. Xu, C. Tovey and G. Sharon. Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios. In Proceedings of IJCAI-16 Workshop on Multi-Agent Path Finding, 2016.
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-w orld scenarios and four research directions that address them. We emphasize the importance of addressing these issues as opposed to dev eloping faster methods for the standard formulation of the MAPF problem.
Download the paper in pdf.
Many publishers do not want authors to make their papers available electronically after the papers have been published. Please use the electronic versions provided here only if hardcopies are not yet available. If you have comments on any of these papers, please send me an email! Also, please send me your papers if we have common interests.
This page was automatically created by a bibliography maintenance system that was developed as part of an undergraduate research project, advised by Sven Koenig.