基于CBR的信息系统案例检索多Agent模型研究

Research on multi-Agent system model for case retrieval of information systems based on CBR

将Multi-Agent技术应用于信息系统案例检索中,结合CBR技术与Web Service思想,提出了基于CBR的信息系统案例检索多Agent系统的模型框架和运作流程,设计了基于智能聚类的案例检索算法,通过神经网络的自组织学习优化案例检索的过程,使得该多Agent系统成为具有高度自治性的自我学习与完善的系统,为信息系统案例检索系统的研究与开发提供了一定的借鉴。

The multi-Agent technique is introduced into the case retrieval of information systems. With the combination of CBR technique and web service, the framework of CBR based multi-Agent system model for case retrieval of information systems is put forward and the operating process is analyzed. Based on the theory of self-organization neural network the intelligent clustering based case retrieval algorithm of information systems is studied, which makes the multi-Agent system highly autonomous and self-adaptive. The research work is a reference to the research and development of the case retrieval of information systems.