A dynamic optimization decision and control model based on neighborhood systems

In order to imitate the dynamic decision and action mode of intelligent creatures responding to environmental changes, this paper presents a dynamic decision and control model based on neighborhood systems. Whose main idea is to break down a decision-making process which is dynamic and complex from a macro point of view, into a series of static decision-making processes which are simple from a microscopic point of view. Firstly, we suggest some methods to integrate neighborhood systems located in different metric spaces into one neighborhood system, and present two general models to describe the neighborhood systems and the differential neighborhood systems in normed linear spaces, respectively. Secondly, we propose a general programming model to select the optimal feasible neighborhood and satisfactory feasible neighborhood within neighborhood systems. The optimal or satisfactory neighborhood is just a simple region to make a decision or control action. And present a condition that the overall optimal control can be decomposed into the local optimal control. Finally, a decision-making process based neighborhood systems is shown in steps. The effectiveness of the presented models and methods are illustrated with an intelligent driving system.