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Distributed Nash Equilibrium Seeking Dynamics With Discrete Communication.

Rui Yu, Yutao Tang, Peng Yi

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    |September 7, 2022
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    Summary
    This summary is machine-generated.

    This study presents a distributed algorithm for agents to find Nash equilibrium in games using discrete communications. It proves exponential convergence for periodic and event-triggered communication schemes.

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    Area of Science:

    • Control Theory
    • Distributed Systems
    • Game Theory

    Background:

    • Agents in a network seek Nash equilibrium in noncooperative games.
    • Real-time global information is unavailable; agents rely on neighbor data.
    • Continuous-time dynamics are used, but communication occurs at discrete instants.

    Purpose of the Study:

    • Develop a distributed Nash equilibrium seeking algorithm with discrete communications.
    • Analyze the performance of periodic and event-triggered communication schemes.
    • Reduce communication load while ensuring convergence.

    Main Methods:

    • Designed a continuous-time dynamics for agent variable updates.
    • Implemented periodic communication at fixed intervals.
    • Proposed an event-triggered communication scheme with a periodic event detection mechanism.

    Main Results:

    • Proved the solvability of Nash equilibrium seeking with discrete communications.
    • Demonstrated exponential convergence for all three discrete communication schemes.
    • Comparative simulations validated algorithm performance across schemes and parameters.

    Conclusions:

    • Distributed Nash equilibrium seeking is achievable with discrete communications.
    • Event-triggered and periodic event detection schemes reduce communication overhead.
    • The proposed algorithms ensure robust convergence in networked game scenarios.