A mean-field stochastic maximum principle via Malliavin calculus

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Mean-field stochastic linear quadratic optimal control problems: closed-loop solvability (2016, unknown): “See, for examples, McKean [16], Buckdahn–Djehiche–Li–Peng [5], Buckdahn–Li–Peng [6], Andersson–Djenhiche [2], Buckdahn–Djehiche–Li [4], Meyer-Brandis–Øksendal–Zhou [17], Yong [25], Elliott–Li–Ni [10], Cui–Li–Li [9], Huang–Li–Wang [11], Huang–Li–Yong [12].”
Linear Quadratic Optimal Control Problems for Mean-Field Backward Stochastic Differential Equations (2016, background): “Typical representatives include, but not limited to, McKean [16], Dawson [10], Chan [7], Buckdahn–Djehiche–Li–Peng [5], Buckdahn–Li–Peng [6], Borkar–Kumar [3], Crisan–Xiong [9], Andersson–Djehiche [2], Buckdahn–Djehiche–Li [4], Meyer-Brandis–Oksendal–Zhou [17], Department of Applied Mathematics, The”
A probabilistic weak formulation of mean field games and applications (2013, background): “Early forms of a stochastic maximum principle for this new type of control problem were given in [4, 7, 34].”