Robust linear quadratic mean field social control: A direct approach
ESAIM: Control, Optimisation and Calculus of Variations, Tome 27 (2021), article no. 20

This paper investigates a robust linear quadratic mean field team control problem. The model involves a global uncertainty drift which is common for a large number of weakly-coupled interactive agents. All agents treat the uncertainty as an adversarial agent to obtain a “worst case” disturbance. The direct approach is applied to solve the robust social control problem, where the state weight is allowed to be indefinite. Using variational analysis, we first obtain a set of forward-backward stochastic differential equations (FBSDEs) and the centralized controls which contain the population state average. Then the decentralized feedback-type controls are designed by mean field heuristics. Finally, the relevant asymptotically social optimality is further proved under proper conditions.

DOI : 10.1051/cocv/2021021
Classification : 49N10, 49N70, 91A12, 93E03
Keywords: Mean field game, model uncertainty, linear quadratic control, social optimality, forward-backward stochastic differential equation
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Xie, Tinghan; Wang, Bing-Chang; Huang, Jianhui. Robust linear quadratic mean field social control: A direct approach. ESAIM: Control, Optimisation and Calculus of Variations, Tome 27 (2021), article no. 20. doi: 10.1051/cocv/2021021

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Cité par Sources :

The first author acknowledges the financial support from: P0008686, P0031044. The second author acknowledges the support from: NNSF of China (61773241), the Youth Innovation Group Project of Shandong University (2020QNQT016). The third author acknowledges the support from: RGC 153005/14P, 153275/16P, P0030808. The authors also acknowledge the support from: The PolyU-SDU Joint Research Centre on Financial Mathematics.