  We consider the stochastic optimal control problem of nonlinear mean-field
systems in discrete time. We reformulate the problem into a deterministic
control problem with marginal distribution as controlled state variable, and
prove that dynamic programming principle holds in its general form. We apply
our method for solving explicitly the mean-variance portfolio selection and the
multivariate linear-quadratic McKean-Vlasov control problem.
