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

作　　者：黄伟栋[1] 王小平[1] 曹立明[1] 

机构地区：[1]同济大学计算机科学与工程系,上海200092

出　　处：《计算机工程》2004年第1期62-64,106,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(70171061)

摘　　要：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.

关 键 词：自适应系统 组织学习 主体 遗传学习 复杂性 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]