A Fast Policy Search Models for Control

Two of the key challenges when applying traditional control and reinforcement learning methods are the need for (I) an appropriate reward function, and (II) a dynamics model that is sufficiently accurate. This paper focuses on the problem that estimate the dynamics model from a given data set already collected from the system and the problem that how to improve iteration speed. For control system, optimal parameters and policies are calculated through iteration.