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Non-Refined Abstractions in Counterexample Guided Abstraction Refinement for Multi-Agent Path Finding (Extended Abstract)

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F24%3A00381968" target="_blank" >RIV/68407700:21240/24:00381968 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1609/socs.v17i1.31584" target="_blank" >https://doi.org/10.1609/socs.v17i1.31584</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1609/socs.v17i1.31584" target="_blank" >10.1609/socs.v17i1.31584</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Non-Refined Abstractions in Counterexample Guided Abstraction Refinement for Multi-Agent Path Finding (Extended Abstract)

  • Original language description

    Counterexample guided abstraction refinement (CEGAR) represents a powerful symbolic technique for various tasks such as model checking and reachability analysis. Recently, CEGAR combined with Boolean satisfiability (SAT) has been applied for multi-agent path finding (MAPF), a problem where the task is to navigate agents from their start positions to given individual goal positions so that agents do not collide with each other. The recent CEGAR approach used the initial abstraction of the MAPF problem where collisions between agents were omitted and were eliminated in subsequent abstraction refinements. We propose in this work a novel CEGAR-style solver for MAPF based on SAT in which some abstractions are deliberately left non-refined. This adds the necessity to post-process the answers obtained from the underlying SAT solver as these answers slightly differ from the correct MAPF solutions. Non-refining however yields order-of-magnitude smaller SAT encodings than those of the previous approach and speeds up the overall solving process.

  • 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

    <a href="/en/project/GA22-31346S" target="_blank" >GA22-31346S: logicMOVE: Logic Reasoning in Motion Planning for Multiple Robotic Agents</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

    Proceedings of the Seventeenth International Symposium on Combinatorial Search (SoCS 2024)

  • ISBN

    978-1-57735-891-6

  • ISSN

    2832-9171

  • e-ISSN

    2832-9163

  • Number of pages

    2

  • Pages from-to

    287-288

  • Publisher name

    AAAI Press

  • Place of publication

    Menlo Park

  • Event location

    Kananaskis

  • Event date

    Jun 6, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article