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Polarization and Coherence in Mean Field Games Driven by Private and Social Utility

Author

Listed:
  • Paolo Dai Pra

    (University of Verona)

  • Elena Sartori

    (University of Padova)

  • Marco Tolotti

    (Ca’ Foscari University of Venice)

Abstract

We study a mean field game in continuous time over a finite horizon, T, where the state of each agent is binary and where players base their strategic decisions on two, possibly competing, factors: the willingness to align with the majority (conformism) and the aspiration of sticking with the own type (stubbornness). We also consider a quadratic cost related to the rate at which a change in the state happens: changing opinion may be a costly operation. Depending on the parameters of the model, the game may have more than one Nash equilibrium, even though the corresponding N-player game does not. Moreover, it exhibits a very rich phase diagram, where polarized/unpolarized, coherent/incoherent equilibria may coexist, except for T small, where the equilibrium is always unique. We fully describe such phase diagram in closed form and provide a detailed numerical analysis of the N-player counterpart of the mean field game. In this finite dimensional setting, the equilibrium selected by the population of players is always coherent (favoring the subpopulation whose type is aligned with the initial condition), but it does not necessarily minimize the cost functional. Rather, it seems that, among the coherent ones, the equilibrium prevailing is the one that most benefits the underdog subpopulation forced to change opinion.

Suggested Citation

  • Paolo Dai Pra & Elena Sartori & Marco Tolotti, 2023. "Polarization and Coherence in Mean Field Games Driven by Private and Social Utility," Journal of Optimization Theory and Applications, Springer, vol. 198(1), pages 49-85, July.
  • Handle: RePEc:spr:joptap:v:198:y:2023:i:1:d:10.1007_s10957-023-02233-0
    DOI: 10.1007/s10957-023-02233-0
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    References listed on IDEAS

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    1. Lawrence Blume & Steven Durlauf, 2003. "Equilibrium Concepts for Social Interaction Models," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 193-209.
    2. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    3. Dario Bauso & Raffaele Pesenti & Marco Tolotti, 2016. "Opinion Dynamics and Stubbornness Via Multi-Population Mean-Field Games," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 266-293, July.
    4. Huibing Yin & Prashant Mehta & Sean Meyn & Uday Shanbhag, 2014. "On the Efficiency of Equilibria in Mean-Field Oscillator Games," Dynamic Games and Applications, Springer, vol. 4(2), pages 177-207, June.
    5. Erhan Bayraktar & Xin Zhang, 2019. "On non-uniqueness in mean field games," Papers 1908.06207, arXiv.org, revised Mar 2020.
    6. René Carmona & Christy V. Graves, 2020. "Jet Lag Recovery: Synchronization of Circadian Oscillators as a Mean Field Game," Dynamic Games and Applications, Springer, vol. 10(1), pages 79-99, March.
    7. Paolo Dai Pra & Elena Sartori & Marco Tolotti, 2019. "Climb on the Bandwagon: Consensus and Periodicity in a Lifetime Utility Model with Strategic Interactions," Dynamic Games and Applications, Springer, vol. 9(4), pages 1061-1075, December.
    8. Dockner,Engelbert J. & Jorgensen,Steffen & Long,Ngo Van & Sorger,Gerhard, 2000. "Differential Games in Economics and Management Science," Cambridge Books, Cambridge University Press, number 9780521637329.
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