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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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.
AbstractList 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.
Author Hoenig, Wolfgang
Tovey, Craig
Ayanian, Nora
Cohen, Liron
Koenig, Sven
Kumar, T. K. Satish
Xu, Hong
Sharon, Guni
Ma, Hang
Uras, Tansel
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  fullname: Sharon, Guni
BackLink https://doi.org/10.48550/arXiv.1702.05515$$DView paper in arXiv
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Snippet Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues...
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SubjectTerms Computer Science - Artificial Intelligence
Computer Science - Multiagent Systems
Computer Science - Robotics
Title Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios
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