Indefinite Mean-Field Stochastic Linear-Quadratic Optimal Control: From Finite Horizon to Infinite Horizon

In this paper, the finite-horizon and the infinite-horizon indefinite mean-field stochastic linear-quadratic optimal control problems are studied. Firstly, the open-loop optimal control and the closed-loop optimal strategy for the finite-horizon problem are introduced, and their characterizations, difference and relationship are thoroughly investigated. The open-loop optimal control can be defined for a fixed initial state, whose existence is characterized via the solvability of a linear mean-field forward-backward stochastic difference equation with stationary conditions and a convexity condition. On the other hand, the existence of a closed-loop optimal strategy is shown to be equivalent to any one of the following conditions: the solvability of a couple of generalized difference Riccati equations, the finiteness of the value function for all the initial pairs, and the existence of the open-loop optimal control for all the initial pairs. It is then proved that the solution of the generalized difference Riccati equations converges to a solution of a couple of generalized algebraic Riccati equations. By studying another generalized algebraic Riccati equation, the existence of the maximal solution of the original ones is obtained together with the fact that the stabilizing solution is the maximal solution. Finally, we show that the maximal solution is employed to express the optimal value of the infinite-horizon indefinite mean-field linear-quadratic optimal control. Furthermore, for the question whether the maximal solution is the stabilizing solution, the necessary and the sufficient conditions are presented for several cases.