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Engineering Smart Behavior in Evacuation Planning using Local Cooperative Path Finding Algorithms and Agent-based Simulations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F19%3A00333596" target="_blank" >RIV/68407700:21240/19:00333596 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.keod.ic3k.org/" target="_blank" >http://www.keod.ic3k.org/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Engineering Smart Behavior in Evacuation Planning using Local Cooperative Path Finding Algorithms and Agent-based Simulations

  • Original language description

    This paper addresses evacuation problems from the perspective of cooperative path finding (CPF). The evacuation problem we call multi-agent evacuation(MAE) consists of an undirected graph and a set of agents.The task is to move agents from the endangered part of the graph into the safe part as quickly as possible.Although there exist centralized evacuation algorithms based on network flows that are optimal with respect to various objectives, such algorithms would hardly be applicable in practice since real agents will not be able to follow the centrally created plan. Therefore we designed a local evacuation planning algorithm called LC-MAE based on local CPF techniques. Agent-based simulations in multiple real-life scenarios show that LC-MAE produces solutions that are only worse than the optimum by a small factor. Moreover our approach led to important findings about how many agents need to behave rationally to increase the speed of evacuation.

  • 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

    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

    Proceedings of the 11th International Conference on Knowledge Engineering and Ontology Development

  • ISBN

    978-989-758-382-7

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    137-142

  • Publisher name

    SciTePress - Science and Technology Publications

  • Place of publication

    Porto

  • Event location

    Vídeň

  • Event date

    Sep 17, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article