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Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios
February 17, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Hang Ma, Sven Koenig, Nora Ayanian, Liron Cohen, Wolfgang Hoenig, T. K. Satish Kumar, Tansel Uras, Hong Xu, Craig Tovey, Guni Sharon
arXiv ID
1702.05515
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.MA,
cs.RO
Citations
98
Venue
arXiv.org
Last Checked
3 months ago
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.
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