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http://hdl.handle.net/10397/93874
Title: | Robust linear quadratic mean field social control : a direct approach | Authors: | Xie, T Wang, BC Huang, J |
Issue Date: | 2021 | Source: | ESAIM. Control, optimisation and calculus of variations, 2021, v. 27, 20 | Abstract: | 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. | Keywords: | Forward-backward stochastic differential equation Linear quadratic control Mean field game Model uncertainty Social optimality |
Publisher: | EDP Sciences | Journal: | ESAIM. Control, optimisation and calculus of variations | ISSN: | 1292-8119 | EISSN: | 1262-3377 | DOI: | 10.1051/cocv/2021021 | Rights: | © EDP Sciences, SMAI 2021 The original publication is available at https://www.esaim-cocv.org/. The following publication Xie, T., Wang, B. C., & Huang, J. (2021). Robust linear quadratic mean field social control: A direct approach. ESAIM: Control, Optimisation and Calculus of Variations, 27, 20 is available at https://doi.org/10.1051/cocv/2021021 |
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