Relationships Between the Maximum Principle and Dynamic Programming for Infinite Dimensional Non-Markovian Stochastic Control Systems
This paper investigates the relationship between Pontryagin's maximum principle and dynamic programming principle in the context of stochastic optimal control systems governed by stochastic evolution equations with random coefficients in separable Hilbert spaces. Our investigation proceeds through three contributions: (1). We first establish the formulation of the dynamic programming principle for this class of infinite-dimensional stochastic systems, subsequently deriving the associated stochastic Hamilton-Jacobi-Bellman equations that characterize the value function's evolution. (2). For systems with smooth value functions, we develop explicit correspondence relationships between Pontryagin's maximum principle and dynamic programming principle, elucidating their fundamental connections through precise mathematical characterizations. (3). In the more challenging non-smooth case, we employ tools in nonsmooth analysis and relaxed transposition solution techniques to uncover previously unknown sample-wise relationships between the two principles.