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Dynamic Optimization of Large-Population Systems with Partial Information

Author

Listed:
  • Jianhui Huang

    (The Hong Kong Polytechnic University)

  • Shujun Wang

    (The Hong Kong Polytechnic University)

Abstract

We consider the dynamic optimization of large-population system with partial information. The associated mean-field game is formulated, and its consistency condition is equivalent to the wellposedness of some Riccati equation system. The limiting state-average is represented by a mean-field stochastic differential equation driven by the common Brownian motion. The decentralized strategies with partial information are obtained, and the approximate Nash equilibrium is verified.

Suggested Citation

  • Jianhui Huang & Shujun Wang, 2016. "Dynamic Optimization of Large-Population Systems with Partial Information," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 231-245, January.
    • Handle: RePEc:spr:joptap:v:168:y:2016:i:1:d:10.1007_s10957-015-0740-x
    DOI: 10.1007/s10957-015-0740-x
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    Cited by:

    1. Masashi Sekine, 2024. "Mean field equilibrium asset pricing model under partial observation: An exponential quadratic Gaussian approach," Papers 2410.01352, arXiv.org.

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