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

Přehled o publikaci

D 2023

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

KLAŠKA, David; Antonín KUČERA; Martin KUREČKA; Vít MUSIL; Petr NOVOTNÝ et al.

Basic information

Original name

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

Authors

KLAŠKA, David; Antonín KUČERA; Martin KUREČKA; Vít MUSIL; Petr NOVOTNÝ and Vojtěch ŘEHÁK

Edition

Neuveden, Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023, p. 171-179, 9 pp. 2023

Publisher

International Joint Conferences on Artificial Intelligence

Other information

Language

English

Type of outcome

Proceedings paper

Confidentiality degree

is not subject to a state or trade secret

Publication form

electronic version available online

References:

URL

Marked to be transferred to RIV

Yes

RIV identification code

RIV/00216224:14330/23:00131516

Organization

Fakulta informatiky – Repository – Repository

ISBN

978-1-956792-03-4

ISSN

Keywords in English

Multi-agent systems; strategy synthesis

Links

GA23-06963S, research and development project. MUNI/A/1081/2022, interní kód Repo. MUNI/A/1433/2022, interní kód Repo. 0011629866, interní kód Repo. 101087529, interní kód Repo.

Changed: 29/7/2025 00:50, RNDr. Daniel Jakubík

Abstract

In the original language

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.

Files attached

https://is.muni.cz/publication/2304578/paper.pdf File version

Cite

KLAŠKA, David; Antonín KUČERA; Martin KUREČKA; Vít MUSIL; Petr NOVOTNÝ and Vojtěch ŘEHÁK. Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems. Online. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023,. Neuveden: International Joint Conferences on Artificial Intelligence, 2023, p. 171-179. ISBN 978-1-956792-03-4. Available from: https://doi.org/10.24963/ijcai.2023/20.

@inproceedings{62706,
   author = {Klaška, David and Kučera, Antonín and Kurečka, Martin and Musil, Vít and Novotný, Petr and Řehák, Vojtěch},
   address = {Neuveden},
   booktitle = {Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023,},
   doi = {https://doi.org/10.24963/ijcai.2023/20},
   keywords = {Multi-agent systems; strategy synthesis},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Neuveden},
   isbn = {978-1-956792-03-4},
   pages = {171-179},
   publisher = {International Joint Conferences on Artificial Intelligence},
   title = {Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems},
   url = {https://www.ijcai.org/proceedings/2023/20},
   year = {2023}
}

TY  - CONF
ID  - 62706
AU  - Klaška, David - Kučera, Antonín - Kurečka, Martin - Musil, Vít - Novotný, Petr - Řehák, Vojtěch
PY  - 2023
TI  - Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems
PB  - International Joint Conferences on Artificial Intelligence
CY  - Neuveden
SN  - 9781956792034
KW  - Multi-agent systems
KW  - strategy synthesis
UR  - https://www.ijcai.org/proceedings/2023/20
N2  - 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.
ER  -

KLAŠKA, David; Antonín KUČERA; Martin KUREČKA; Vít MUSIL; Petr NOVOTNÝ and Vojtěch ŘEHÁK. Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems. Online. In \textit{Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023,}. Neuveden: International Joint Conferences on Artificial Intelligence, 2023, p.~171-179. ISBN~978-1-956792-03-4. Available from: https://doi.org/10.24963/ijcai.2023/20.

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