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Adversarial Multi-Agent Path Finding is Intractable

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00356868" target="_blank" >RIV/68407700:21240/21:00356868 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/ICTAI52525.2021.00078" target="_blank" >https://doi.org/10.1109/ICTAI52525.2021.00078</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICTAI52525.2021.00078" target="_blank" >10.1109/ICTAI52525.2021.00078</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Adversarial Multi-Agent Path Finding is Intractable

  • Original language description

    Adversarial Multi-Agent Path Finding (AMAPF) extends the standard discrete Multi-Agent Path Finding with an adversarial element. Agents of two competing teams are deployed in a shared environment represented by an undirected graph. The first team aims to navigate all its agents from their initial locations to given goal locations, while the second team aims to prevent agents of the first team from fulfilling their goal. We prove that the problem of finding a winning strategy is EXPTIME-complete.

  • 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/GA19-17966S" target="_blank" >GA19-17966S: intALG-MAPFg: Intelligent Algorithms for Generalized Variants of Multi-Agent Path Finding</a><br>

  • Continuities

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

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)

  • ISBN

    978-1-6654-0898-1

  • ISSN

    1082-3409

  • e-ISSN

    2375-0197

  • Number of pages

    6

  • Pages from-to

    481-486

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Los Alamitos

  • Event location

    Washington

  • Event date

    Nov 1, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000747482300070