McKean-Vlasov Optimal Control: Limit Theory and Equivalence Between Different Formulations

• 成果类型: Article; Early Access
• 署名作者: Djete, Mao Fabrice; Possamai, Dylan; Tan, Xiaolu
• 署名单位: Institut Polytechnique de Paris; Ecole Polytechnique; ENSTA Paris; Chinese University of Hong Kong
• 刊物名称: MATHEMATICS OF OPERATIONS RESEARCH
• ISSN/ISSBN: 0364-765X
• DOI: 10.1287/moor.2021.1232
• 发表日期: 2022
• 关键词: mean-field games; inconsistent stochastic-control; invariance-principle; martingale approach; large numbers; systems; propagation; chaos; weak; DIFFUSIONS

摘要

We study a McKean???Vlasov optimal control problem with common noise in order to establish the corresponding limit theory as well as the equivalence between different formulations, including strong, weak, and relaxed formulations. In contrast to the strong formulation, in which the problem is formulated on a fixed probability space equipped with two Brownian filtrations, the weak formulation is obtained by considering a more general probability space with two filtrations satisfying an (H)-hypothesis type condition from the theory of enlargement of filtrations. When the common noise is uncontrolled, our relaxed formulation is obtained by considering a suitable controlled martingale problem. As for classic optimal control problems, we prove that the set of all relaxed controls is the closure of the set of all strong controls when considered as probability measures on the canonical space. Consequently, we obtain the equivalence of the different formulations of the control problem under additional mild regularity conditions on the reward functions. This is also a crucial technical step to prove the limit theory of the McKean???Vlasov control problem, that is, proving that it consists in the limit of a large population control problem with common noise.