Robust mean field linear-quadratic-Gaussian games with unknown L2-disturbance

Jianhui Huang, Minyi Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 Citations (Scopus)


This paper considers a class of mean field linear-quadratic-Gaussian games with model uncertainty. The drift term in the dynamics of the agents contains a common unknown function. We take a robust optimization approach where a representative agent in the limiting model views the drift uncertainty as an adversarial player. By including the mean field dynamics in an augmented state space, we solve two optimal control problems sequentially, which combined with consistent mean field approximations provides a solution to the robust game. A set of decentralized control strategies is derived by use of forward-backward stochastic differential equations and is shown to be a robust "-Nash equilibrium.

Original languageEnglish
Pages (from-to)2811-2840
Number of pages30
JournalSIAM Journal on Control and Optimization
Issue number5
Publication statusPublished - 14 Sept 2017


  • Decentralized control
  • Mean field game
  • Model uncertainty
  • Nash equilibrium
  • Robust control

ASJC Scopus subject areas

  • Control and Optimization
  • Applied Mathematics


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