Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios

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...

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Main Authors Ma, Hang, Koenig, Sven, Ayanian, Nora, Cohen, Liron, Hoenig, Wolfgang, Kumar, T. K. Satish, Uras, Tansel, Xu, Hong, Tovey, Craig, Sharon, Guni
Format Journal Article
LanguageEnglish
Published 17.02.2017
Subjects
Computer Science - Artificial Intelligence
Computer Science - Multiagent Systems
Computer Science - Robotics
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Summary: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.
DOI:10.48550/arxiv.1702.05515