一种基于组织学习的自适应Agent系统体系结构

An Adaptive Architecture of Agent System Based on Organizational Learning

在复杂适应系统和组织学习理论的基础上，探讨了一种基于组织学习的自适应A gent系统体系结构。 在这种体系结构中,通过Agent交互中的适应性行为获取对系统复杂性 的认知，而Agent的适应能力则依靠增强学习和动态自组织与重构来实现。文中给出了一个 基于组织增长模型的分类器系统算法以及相应的软件实现技术途径。

Based on the investigation of complex adaptive system and organizati on learning, this paper discusses an adaptive agent system architecture based on organizational learning, where system adaptive behaviors are supposed to emerge from agent interactions in the interests of knowledge acquisition of system com plexity, and agent adaptability can be achieved by two ways: reinforcement learn ing, dynamical self-organization and reconstruction. In addition, a classifier a lgorithm based on organizational growth model and its software implementation sc heme on Grasshopper platform are given.