Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00131516" target="_blank" >RIV/00216224:14330/23:00131516 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.ijcai.org/proceedings/2023/20" target="_blank" >https://www.ijcai.org/proceedings/2023/20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.24963/ijcai.2023/20" target="_blank" >10.24963/ijcai.2023/20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems

Popis výsledku v původním jazyce

We consider the problem of synthesizing resilient and stochastically stable strategies for systems of cooperating agents striving to minimize the expected time between consecutive visits to selected locations in a known environment. A strategy profile is resilient if it retains its functionality even if some of the agents fail, and stochastically stable if the visiting time variance is small. We design a novel specification language for objectives involving resilience and stochastic stability, and we show how to efficiently compute strategy profiles (for both autonomous and coordinated agents) optimizing these objectives. Our experiments show that our strategy synthesis algorithm can construct highly non-trivial and efficient strategy profiles for environments with general topology.

Název v anglickém jazyce

Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems

Popis výsledku anglicky

We consider the problem of synthesizing resilient and stochastically stable strategies for systems of cooperating agents striving to minimize the expected time between consecutive visits to selected locations in a known environment. A strategy profile is resilient if it retains its functionality even if some of the agents fail, and stochastically stable if the visiting time variance is small. We design a novel specification language for objectives involving resilience and stochastic stability, and we show how to efficiently compute strategy profiles (for both autonomous and coordinated agents) optimizing these objectives. Our experiments show that our strategy synthesis algorithm can construct highly non-trivial and efficient strategy profiles for environments with general topology.

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/GA23-06963S" target="_blank" >GA23-06963S: VESCAA: Verifikovatelná a efektivní syntéza kontrolerů pro autonomní agenty</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023,

ISBN

9781956792034

ISSN

1045-0823

e-ISSN

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Počet stran výsledku

9

Strana od-do

171-179

Název nakladatele

International Joint Conferences on Artificial Intelligence

Místo vydání

Neuveden

Místo konání akce

Macao

Datum konání akce

1. 1. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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