第8卷第2期 智能系统学报 Vol.8 No.2 2013年4月 CAAI Transactions on Intelligent Systems Apr.2013 D0I:10.3969/i.issn.16734785.201210043 网络出版t地址：htp://www.cnki.net/kcma/detail/23.1538.TP.20130409.1436.003.html 基于Agent的专家系统推理模型 陶倩，马刚2，史忠植2 (1.上海体育学院体有赛事研究中心，上海200438；2.中国科学院计算技术研究所智能信息处理重点实验室，北京 100190) 摘要：针对传统专家系统推理模型结构在知识获取方面适应性差的现状，从系统科学的视角，运用复杂适应系统 理论，对传统专家系统的结构及运行机制进行了改进.引入Aget来模拟人脑中的神经元，用来承载专家系统中相互 作用的知识，然后，基于Mli-Aget之间的相互作用来构建复杂适应的专家系统推理模型.从而，将专家系统中的知 识获取机制、知识库、推理机三者统一于由Mt-Agt进行相互作用的复杂适应系统之中.通过设计体育赛事申办 决策专家系统的原型，进行了专家系统推理模型的验证.原型运行结果表明：基于Muli-Aget的专家系统推理模型 结构能够有效地提高专家系统知识获取的适应性.这为研究更加接近人脑智能的专家系统提供了崭新的研究思路。 关键词：Agent:推理模型；专家系统；体育赛事 中图分类号：TP391.6文献标志码：A文章编号：16734785(2013)02-013508 Research on the expert system reasoning model based on Agent TAO Qian',MA Gang2,SHI Zhongzhi2 (1.The Sports Event Research Center of Shanghai University of Sport,Shanghai 200438,China;2.Key Laboratory of Intelligent In- formation Processing,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China) Abstract:The traditional expert system reasoning model structure has poor adaptability in acquiring knowledge. From the viewpoint of system science,the complex adaptive system theory is used to improve the structure and oper- ation mechanism of a traditional expert system.Firstly,an Agent was introduced to simulate neurons in the human brain and load the knowledge interacting in the expert system reasoning model.Then an expert system reasoning model of complex adaptation was constructed based on the Multi-Agent interaction.Consequently,the knowledge acquiring mechanism,knowledge base and reasoning engine were unified into the Agents interaction in the complex adaptive expert system.Finally,by designing the expert system reasoning model prototype in decision-making of in- ternational sporting events bidding,the effectiveness of the expert system reasoning model based on Agent was veri- fied.The results of the prototype running show that the expert system reasoning structure based on Multi-Agent model can effectively improve the adaptability of expert system knowledge acquisition.That provides a new idea for studying the expert system closer to human intelligence. Keywords:Agent;reasoning model;expert system;sporting events 专家系统推理模型是对人类专家推理能力的建 进展和成果[19.然而，随着研究的不断深入，人们 模，其经过50余年的发展，已经取得了许多重要的 发现，目前的专家系统推理模型并不能很好地模拟 人类专家的推理能力，尤其是在对知识的获取上，还 收稿日期：2012-10-21.网络出版日期：2013-0409 需依靠知识工程师先去理解领域专家的知识，并预 基金项目：国家“973”计划资助项日(2013CB329502):国家“863”计 先输入到专家系统的知识库中.专家系统推理模型 划资助项目(2012AA011003);国家自然科学基金资助项 目(61035003,61202212,60933004)：国家科技支撑计划 的推理机制与知识库中的具体知识密切相关.因而， 资助项目(2012BA107B02). 通信作者：陶情.E-mail:taoqian_101010@163.com 在专家系统后续运行的过程中很难进行适应性的补