A Stochastic Maximum Principle for a Minimization Problem Under Partial Information

In this paper, we establish a stochastic maximum principle for minimization problem under partial information. With the Backward differential equations (in short BSDE’s), sufficient condition of optimality to characterize and determine an optimal control. This is done instead using Hamiltonian which deterministic function. The translating dynamics state variables controlled system contain BSPDE (Backward equation) can be unnormalized conditional density like Zakai equation born from passage full