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Multi-Agent Path Finding – An Overview

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Artificial Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11866))

Abstract

Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. In recent years, there has been a growing interest in MAPF in the Artificial Intelligence (AI) research community. This interest is partially because real-world MAPF applications, such as warehouse management, multi-robot teams, and aircraft management, are becoming more prevalent. In this overview, we discuss several possible definitions of the MAPF problem. Then, we survey MAPF algorithms, starting with fast but incomplete algorithms, then fast, complete but not optimal algorithms, and finally optimal algorithms. Then, we describe approximately optimal algorithms and conclude with non-classical MAPF and pointers for future reading and future work.

Supported by ISF grant 210/17 to Roni Stern.

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Notes

  1. 1.

    The exact definition of slidable is slightly more involved. The interested reader can see the exact definition in Wang and Botea’s paper [49].

  2. 2.

    This is actually a description of the simple ID algorithm. In the full ID algorithm, the conflicting agents attempt to individually avoid the conflict while maintaining their original solution cost.

  3. 3.

    Actually, this constraint only prevents vertex conflicts. To prevent swapping conflicts, an additional constraint is needed, in which for every time step t before T, pair of agents a and \(a'\), and pair of locations v and \(v'\), if the variables \(\mathcal {X}_{i,t,v}\) and \(\mathcal {X}_{i,t',v'}\) are both true then the variables \(\mathcal {X}_{j,t,v'}\) and \(\mathcal {X}_{j,t',v}\) must not be both true.

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Authors and Affiliations

  1. Ben Gurion University of the Negev, Be’er Sheva, Israel

    Roni Stern

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  1. Roni Stern
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Correspondence to Roni Stern .

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  1. Federal Research Center "Computer Science and Control", Moscow, Russia

    Gennady S. Osipov

  2. Federal Research Center "Computer Science and Control", Moscow, Russia

    Aleksandr I. Panov

  3. Federal Research Center "Computer Science and Control", Moscow, Russia

    Konstantin S. Yakovlev

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Stern, R. (2019). Multi-Agent Path Finding – An Overview. In: Osipov, G., Panov, A., Yakovlev, K. (eds) Artificial Intelligence. Lecture Notes in Computer Science(), vol 11866. Springer, Cham. https://doi.org/10.1007/978-3-030-33274-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-33274-7_6

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