A mean-field stochastic maximum principle via Malliavin calculus

This paper considers a mean-field type stochastic control problem where the dynamics is governed by a controlled Itô-Lévy process and the information available to the controller is possibly less than the overall information. All the system coefficients and the objective performance functional are allowed to be random, possibly non-Markovian. Malliavin calculus is employed to derive a maximum principle for the optimal control of such a system where the adjoint process is explicitly expressed. © 2012 Copyright Taylor and Francis Group, LLC