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A dynamic optimization decision and control model based on neighborhood systems

机译:基于邻域系统的动态优化决策与控制模型

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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.
机译:为了模仿智能生物对环境变化的动态决策和行动模式,提出了一种基于邻域系统的动态决策和控制模型。其主要思想是将从宏观角度来看动态而复杂的决策过程分解为一系列从微观角度来看很简单的静态决策过程。首先,我们提出了一些将位于不同度量空间的邻域系统集成到一个邻域系统中的方法,并提出了两种通用模型分别描述了赋范线性空间中的邻域系统和差分邻域系统。其次,我们提出了一个通用的编程模型来在邻域系统中选择最优可行邻域和满意可行邻域。最佳或令人满意的邻域只是做出决定或控制行动的简单区域。并提出了将整体最优控制分解为局部最优控制的条件。最后,分步展示了基于决策过程的邻域系统。通过智能驾驶系统说明了所提出模型和方法的有效性。

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