  This paper investigates an infinite-horizon linear quadratic stochastic (LQS)
optimal control problem for a class of continuous-time stochastic systems. By
employing the technique of adaptive dynamic programming (ADP), we propose a
novel model-free policy iteration (PI) algorithm. Without needing all
information of the system coefficient matrices, the proposed PI algorithm
iterates by using the data of the input and system state collected on a fixed
time interval. Finally, a numerical example is presented to demonstrate the
feasibility of the obtained algorithm.
