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

Kód výsledku v 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>

Výsledek na webu

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

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

<a href="/cs/project/GA19-17966S" target="_blank" >GA19-17966S: intALG-MAPFg: Inteligentní algoritmy pro zobecněné varianty multi-agetního hledání cest</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

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

ISBN

978-989-758-382-7

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

137-142

Název nakladatele

SciTePress - Science and Technology Publications

Místo vydání

Porto

Místo konání akce

Vídeň

Datum konání akce

17. 9. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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