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Master equation of discrete-time Stackelberg mean field games with multiple leaders

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  • Deepanshu Vasal

Abstract

In this paper, we consider a discrete-time Stackelberg mean field game with a finite number of leaders, a finite number of major followers and an infinite number of minor followers. The leaders and the followers each observe types privately that evolve as conditionally independent controlled Markov processes. The leaders are of "Stackelberg" kind which means they commit to a dynamic policy. We consider two types of followers: major and minor, each with a private type. All the followers best respond to the policies of the Stackelberg leaders and each other. Knowing that the followers would play a mean field game (with major players) based on their policy, each (Stackelberg) leader chooses a policy that maximizes her reward. We refer to the resulting outcome as a Stackelberg mean field equilibrium with multiple leaders (SMFE-ML). In this paper, we provide a master equation of this game that allows one to compute all SMFE-ML. We further extend this notion to the case when there are infinite number of leaders.

Suggested Citation

  • Deepanshu Vasal, 2022. "Master equation of discrete-time Stackelberg mean field games with multiple leaders," Papers 2209.03186, arXiv.org.
  • Handle: RePEc:arx:papers:2209.03186
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    1. Dirk Bergemann & Maher Said, 2010. "Dynamic Auctions: A Survey," Cowles Foundation Discussion Papers 1757, Cowles Foundation for Research in Economics, Yale University.
    2. Victor DeMiguel & Huifu Xu, 2009. "A Stochastic Multiple-Leader Stackelberg Model: Analysis, Computation, and Application," Operations Research, INFORMS, vol. 57(5), pages 1220-1235, October.
    3. Olivier Guéant & Pierre Louis Lions & Jean-Michel Lasry, 2011. "Mean Field Games and Applications," Post-Print hal-01393103, HAL.
    4. Krishnamurthy Iyer & Ramesh Johari & Mukund Sundararajan, 2014. "Mean Field Equilibria of Dynamic Auctions with Learning," Management Science, INFORMS, vol. 60(12), pages 2949-2970, December.
    5. Boonen, Tim J. & Pantelous, Athanasios A. & Wu, Renchao, 2018. "Non-cooperative dynamic games for general insurance markets," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 123-135.
    6. José R. Correa & Andreas S. Schulz & Nicolás E. Stier-Moses, 2004. "Selfish Routing in Capacitated Networks," Mathematics of Operations Research, INFORMS, vol. 29(4), pages 961-976, November.
    7. Maskin, Eric & Tirole, Jean, 2001. "Markov Perfect Equilibrium: I. Observable Actions," Journal of Economic Theory, Elsevier, vol. 100(2), pages 191-219, October.
    8. Deepanshu Vasal & Randall Berry, 2022. "Master Equation for Discrete-Time Stackelberg Mean Field Games with single leader," Papers 2201.05959, arXiv.org.
    9. Adlakha, Sachin & Johari, Ramesh & Weintraub, Gabriel Y., 2015. "Equilibria of dynamic games with many players: Existence, approximation, and market structure," Journal of Economic Theory, Elsevier, vol. 156(C), pages 269-316.
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