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Multi-agent Path Finding with Generalized Conflicts: An Experimental Study

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Agents and Artificial Intelligence (ICAART 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11978))

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Abstract

This paper gives an overview of conflict reasoning in generalizations of multi-agent path finding (MAPF). MAPF and derived variants assume items placed in vertices of an undirected graph with at most one item per vertex. Items can be relocated across edges while various constraints depending on the concrete type of relocation problem must be satisfied. We recall a general problem formulation that encompasses known types of item relocation problems such as multi-agent path finding (MAPF), token swapping (TSWAP), token rotation (TROT), and token permutation (TPERM). We then focused on three existing optimal algorithms for MAPF: search-based CBS, and propositional satisfiability (SAT) - based MDD-SAT and SMT-CBS. These algorithms were modified to tackle various types of conflicts. The major contribution of this paper is a thorough experimental evaluation of CBS, MDD-SAT, and SMT-CBS on various types of relocation problems.

This work has been supported by GAČR - the Czech Science Foundation, grant registration number 19-17966S.

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Notes

  1. 1.

    The presented version of adjacency is sometimes called parallel while a term adjacency is reserved for the case with \(|F|=1\).

  2. 2.

    The notation \(path(a_i)\) refers to path in the form of a seqeunce of vertices and edges connecting \(\alpha _0(a_i)\) and \( \alpha _+(a_i)\) while \(\xi \) assigns the cost to a given path.

  3. 3.

    These problems have been considered in the literature in different contexts already (for example in [56]). But not from the practical solving perspective focused on finding optimal solutions.

  4. 4.

    Formally this is the same as in MAPF, but in addition to this MAPF checks vacancy of the target vertex which may cause more colliding situations.

  5. 5.

    To enable reproducibility of results presented in this paper we provide complete source codes and experimental data on author’s web page: http://users.fit.cvut.cz/surynpav/research/ icaart2019revised.

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Authors and Affiliations

  1. Faculty of Information Technology, Czech Technical University in Prague, Thákurova 9, 160 00, Praha 6, Czech Republic

    Pavel Surynek

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  1. Pavel Surynek
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Correspondence to Pavel Surynek .

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Editors and Affiliations

  1. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  2. LIACC, University of Porto, Porto, Portugal

    Ana Paula Rocha

  3. ICREA, Institute of Evolutionary Biology, Barcelona, Spain

    Luc Steels

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Surynek, P. (2019). Multi-agent Path Finding with Generalized Conflicts: An Experimental Study. In: van den Herik, J., Rocha, A., Steels, L. (eds) Agents and Artificial Intelligence. ICAART 2019. Lecture Notes in Computer Science(), vol 11978. Springer, Cham. https://doi.org/10.1007/978-3-030-37494-5_7

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  • DOI: https://doi.org/10.1007/978-3-030-37494-5_7

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