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Solving Multi-Agent Pathfinding with Stochastic Local Search SAT Algorithms

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F24%3A00379350" target="_blank" >RIV/68407700:21240/24:00379350 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.5220/0012944800003822" target="_blank" >https://doi.org/10.5220/0012944800003822</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0012944800003822" target="_blank" >10.5220/0012944800003822</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Solving Multi-Agent Pathfinding with Stochastic Local Search SAT Algorithms

  • Original language description

    This paper explores the suitability of Stochastic Local Search (SLS) solvers for Multi-Agent Pathfinding (MAPF) translated into the SAT domain. Traditionally, SAT encodings of MAPF have been tackled using Conflict-Driven Clause Learning (CDCL) solvers, but this work investigates the potential of SLS solvers, particularly ProbSAT, in solving MAPF under the makespan objective. By employing the MDD-SAT approach and comparing the performance of ProbSAT against the Glucose 4 CDCL solver, the effects of eager and lazy encodings are evaluated, as well as the benefit of providing initial variable assignments. Results show that ProbSAT can effectively solve MAPF instances, especially when initial assignments based on agents' shortest paths are provided. This study suggests that SLS solvers can compete with CDCL solvers in specific MAPF scenarios and highlights future research directions for optimizing SLS performance in MAPF.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    21st International Conference on Informatics in Control, Automation and Robotics - Volume 1

  • ISBN

    978-989-758-717-7

  • ISSN

    2184-2809

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    67-78

  • Publisher name

    Science and Technology Publications, Lda

  • Place of publication

    Setúbal

  • Event location

    Porto

  • Event date

    Nov 18, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article