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Online Multi-Agent Pathfinding

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10408101" target="_blank" >RIV/00216208:11320/19:10408101 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21730/19:00328779

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Online Multi-Agent Pathfinding

  • Original language description

    Multi-agent pathfinding (MAPF) is the problem of moving a group of agents to a set of target destinations while avoiding collisions. In this work, we study the online version of MAPF where new agents appear over time. Several variants of online MAPF are defined and analyzed theoretically, showing that it is not possible to create an optimal online MAPF solver. Nevertheless, we propose effective online MAPF algorithms that balance solution quality, runtime, and the number of plan changes an agent makes during execution.

  • 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

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

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

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

  • ISBN

    978-1-57735-809-1

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    7732-7739

  • Publisher name

    ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE

  • Place of publication

    PALO ALTO

  • Event location

    Honolulu

  • Event date

    Jan 27, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000486572502033