文献类型：会议论文

英文题名：Teaching resource grid system model based on multi-agent distributed expert system

作者：Xiao, Laisheng[1]; Wang, Zhengxia[2]

机构：[1] Network and Education Technology Center, Guangdong Ocean University, Zhanjiang, China; [2] College of Law, Guangdong Ocean University, Zhanjiang, China

会议论文集：Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

会议日期：December 11, 2009 - December 13, 2009

会议地点：Wuhan, China

语种：英文

外文关键词：Efficiency - Engineering education - Expert systems - Software engineering

外文摘要：A major breakthrough of modern education technology is that it can take full advantage of Internet technology for teaching service. Because of its rich teaching resource and friendly interaction, network teaching has become more and more preferred mode of teaching aid at colleges and universities. In this paper, we firstly introduce the concept of three-dimensional network teaching resource. In order to eliminate the phenomenon of teaching resource islands, we present a teaching resource grid system model based on multi-agent distributed expert system. By means of grid technology, network resource and teaching resource are globally integrated and shared. In this model, we also introduce multi-agent distributed expert system to improve the efficiency of teaching resource retrieval and positioning, as well as to realize the intelligence of knowledge answer. In this way, we have designed a high intelligent teaching resource grid system. The greatest contribution of this paper is that we have proposed the architecture model of grid system with high intelligence for teaching resource. In the end of this paper, we also study organization efficiency and communication efficiency for teaching resource grid system based on multiagent distributed expert system. A method of logical domain management and a sort of mechanism of agent communication alliance have been introduced, which greatly enhances the organization efficiency and the communication efficiency for multi-agent distributed expert system. ?2009 IEEE.