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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Bibliographic Details
Published inarXiv.org
Main Authors Ma, Hang, Koenig, Sven, Ayanian, Nora, Cohen, Liron, Hoenig, Wolfgang, Satish Kumar, T K, Uras, Tansel, Xu, Hong, Tovey, Craig, Guni Sharon
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 17.02.2017
Subjects
Artificial intelligence
Multiagent systems
Operations research
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.
ISSN:2331-8422