Crowd-Averse Cyber-Physical Systems

The Paradigm of Robust Mean-Field Games

Dario Bauso, Tembine Hamidou

    Research output: Contribution to journalArticle

    Abstract

    For a networked controlled system, we illustrate the paradigm of robust mean-field games. This is a modeling framework at the interface of differential game theory, mathematical physics, and H- optimal control that tries to capture the mutual influence between a crowd and its individuals. First, we establish a mean-field system for such games including the effects of adversarial disturbances. Second, we identify the optimal response of the individuals for a given population behavior. Third, we provide an analysis of equilibria and their stability.

    Original languageEnglish (US)
    Article number7300401
    Pages (from-to)2312-2317
    Number of pages6
    JournalIEEE Transactions on Automatic Control
    Volume61
    Issue number8
    DOIs
    StatePublished - Aug 1 2016

    Fingerprint

    Game theory
    Physics
    Cyber Physical System

    Keywords

    • Closed loop systems
    • control design
    • control engineering

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Computer Science Applications
    • Electrical and Electronic Engineering

    Cite this

    Crowd-Averse Cyber-Physical Systems : The Paradigm of Robust Mean-Field Games. / Bauso, Dario; Hamidou, Tembine.

    In: IEEE Transactions on Automatic Control, Vol. 61, No. 8, 7300401, 01.08.2016, p. 2312-2317.

    Research output: Contribution to journalArticle

    Bauso, Dario ; Hamidou, Tembine. / Crowd-Averse Cyber-Physical Systems : The Paradigm of Robust Mean-Field Games. In: IEEE Transactions on Automatic Control. 2016 ; Vol. 61, No. 8. pp. 2312-2317.
    @article{775beaa03d83483c97457f9cf92c8018,
    title = "Crowd-Averse Cyber-Physical Systems: The Paradigm of Robust Mean-Field Games",
    abstract = "For a networked controlled system, we illustrate the paradigm of robust mean-field games. This is a modeling framework at the interface of differential game theory, mathematical physics, and H∞- optimal control that tries to capture the mutual influence between a crowd and its individuals. First, we establish a mean-field system for such games including the effects of adversarial disturbances. Second, we identify the optimal response of the individuals for a given population behavior. Third, we provide an analysis of equilibria and their stability.",
    keywords = "Closed loop systems, control design, control engineering",
    author = "Dario Bauso and Tembine Hamidou",
    year = "2016",
    month = "8",
    day = "1",
    doi = "10.1109/TAC.2015.2492038",
    language = "English (US)",
    volume = "61",
    pages = "2312--2317",
    journal = "IEEE Transactions on Automatic Control",
    issn = "0018-9286",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",
    number = "8",

    }

    TY - JOUR

    T1 - Crowd-Averse Cyber-Physical Systems

    T2 - The Paradigm of Robust Mean-Field Games

    AU - Bauso, Dario

    AU - Hamidou, Tembine

    PY - 2016/8/1

    Y1 - 2016/8/1

    N2 - For a networked controlled system, we illustrate the paradigm of robust mean-field games. This is a modeling framework at the interface of differential game theory, mathematical physics, and H∞- optimal control that tries to capture the mutual influence between a crowd and its individuals. First, we establish a mean-field system for such games including the effects of adversarial disturbances. Second, we identify the optimal response of the individuals for a given population behavior. Third, we provide an analysis of equilibria and their stability.

    AB - For a networked controlled system, we illustrate the paradigm of robust mean-field games. This is a modeling framework at the interface of differential game theory, mathematical physics, and H∞- optimal control that tries to capture the mutual influence between a crowd and its individuals. First, we establish a mean-field system for such games including the effects of adversarial disturbances. Second, we identify the optimal response of the individuals for a given population behavior. Third, we provide an analysis of equilibria and their stability.

    KW - Closed loop systems

    KW - control design

    KW - control engineering

    UR - http://www.scopus.com/inward/record.url?scp=84982735893&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84982735893&partnerID=8YFLogxK

    U2 - 10.1109/TAC.2015.2492038

    DO - 10.1109/TAC.2015.2492038

    M3 - Article

    VL - 61

    SP - 2312

    EP - 2317

    JO - IEEE Transactions on Automatic Control

    JF - IEEE Transactions on Automatic Control

    SN - 0018-9286

    IS - 8

    M1 - 7300401

    ER -