Robust linear quadratic mean field social control: A direct approach

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...

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Bibliographic Details
Published inESAIM. Control, optimisation and calculus of variations Vol. 27; p. 20
Main Authors Xie, Tinghan, Wang, Bing-Chang, Huang, Jianhui
Format Journal Article
LanguageEnglish
Published 2021
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Summary: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.
ISSN:1292-8119
1262-3377
DOI:10.1051/cocv/2021021