[1]TAO Qian,MA Gang,SHI Zhongzhi.Research on the expert system reasoning model based on Agent[J].CAAI Transactions on Intelligent Systems,2013,8(2):135-142.[doi:10.3969/j.issn.1673-4785.201210043]
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Research on the expert system reasoning model based on Agent

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 8 Number of periods: 2013 2 Page number: 135-142 Column: 学术论文—知识工程 Public date: 2013-04-25
Title:
Research on the expert system reasoning model based on Agent
Author(s):
TAO Qian1;  MA Gang2;  SHI Zhongzhi2
1. The Sports Event Research Center of Shanghai University of Sport, Shanghai 200438, China;
2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
Keywords:
Agent;  reasoning model;  expert system;  sporting events
CLC:
TP391.6
DOI:
10.3969/j.issn.1673-4785.201210043
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 operation 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 international sporting events bidding, the effectiveness of the expert system reasoning model based on Agent was verified. 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.
References:
［1］史忠植,王文杰.人工智能［M］.北京：国防工业出版社,2007： 21-30.
［2］邵艳华,张明生.一类复杂适应系统的建模研究［J］.计算机工程, 2012, 38(1): 253-255.
?SHAO Yanhua, ZHANG Mingsheng. Research on a class of complex adaptive system modeling［J］. Computer Engineering, 2012, 38(1): 253-255.
［3］韩业红.基于粗集理论的专家系统中知识的获取、更新与推理［D］.济南：山东师范大学, 2007: 29-35.
HAN Yehong. Knowledge acquisition, modification and reasoning in expert system based on rough set theory［D］.Ji’nan： Shandong Normal University， 2007: 29-35.
［4］钟秀琴，符红光,佘莉，等.基于本体的几何学知识获取及知识表示［J］.计算机学报， 2010, 33(1): 167-174.
?ZHONG Xiuxin, FU Hongguang, SHE Li, et al. Geometry knowledge acquisition and representation on ontology［J］. Chinese Journal of Computers, 2010, 33(1): 167-174.
［5］陈明亮，李怀祖．基于规则的专家系统中不确定性推理的研究［J］．计算机工程与应用， 2000(5): 50-53．
?CHEN Mingliang, LI Huaizhu. Study on the non-accurate inference in expert system based on rule［J］. Computer Engineering and Application, 2000(5): 50-53．
［6］曹珊, 贺正洪. 基于神经网络的专家系统研究及应用［J］. 战术导弹控制技术, 2007, 56(1): 52-55.
?CHAO Shan, HE Zhenghong. Application of expert system based on artificial neural network［J］. Control Technology of Tactical Missile, 2007, 56(1): 52-55.
［7］徐敏,施化吉.基于神经网络集成的专家系统模型［J］.计算机工程与设计, 2006, 27(7):1216-1220.
?XU Min, SHI Huaji. Expert system model based on neural network ensembles［J］. Computer Engineering and Design, 2006, 27(7): 1216-1220.
［8］巩文科，李心广，赵洁．基于BP神经网络与专家系统的故障诊断系统［J］．计算机工程， 2007， 33(8): 199-203.
GONG Wenke, LI Xinguang, ZHAO Jie. Fault diagnosis system based on BP neural network and expert system［J］. Computer Engineering, 2007， 33(8): 199-203.
［9］陈德礼, 程羽. 基于神经网络和规则的专家系统的应用研究［J］. 计算机工程与科学, 2004, 26(6): 70-75.
?CHEN Deli, CHENG Yu. Application research of the ESs based on neural networks and rules［J］. Computer Engineering & Science, 2004, 26(6): 70-75.
［10］陈禹. 复杂性研究的新动向—基于主体的建模方法及其启迪［J］. 系统辨证学学报, 2003, 11(1): 43-50.
?CHEN Yu. A new trend in complexity studies—Agent based modelling and its implication［J］. Journal of Systemic Dialectics, 2003, 11(1): 43-50.
［11］陶倩，徐福缘，黄平. 基于Agent的计算金融学建模方法研究［J］.系统仿真学报， 2008， 20(11): 3004-3007.
?TAO Qian, XU Fuyuan, HUANG Ping. Agent-based computational finance modeling［J］. Journal of System Simulation, 2008, 20(11): 3004-3007.
［12］金士尧, 黄红兵, 范高俊. 面向涌现的多Agent系统研究及其进展［J］.计算机学报, 2008, 31(6): 881-895. JIN Shiyao, HUANG Hongbing, FAN Gaojun. Emergence-oriented research on multi-agent systems and its state of arts［J］. Chinese Journal of Computers, 2008, 31(6): 881-895.
［13］Agent based modeling［EB/OL］. ［2012-08-13］. http://www.cadrc.calpoly.edu/pdf/JSVoss_120400.pdf．
［14］ROBERT A. Advancing the art of simulation in the social sciences［J］. Complexity Magazine, 1987, 3(2): 189-194.
［15］CLAUDIA P W, EBENOTH E. An adaptive toolbox model: a pluralistic modelling approach for human behaviour based on observation［J］. Journal of Artificial Societies and Social Simulation, 2004, 7(1): 176-181.
［16］BOERO R. Some methodological issues of agent based models in social sciences［EB/OL］. ［2012-07-26］.http://www.unisi.it/santachiara/aree/conf_phd_econ2003/conference_ siena/papers/boero.pdf.
［17］SUN R, NAVEH I. Simulating organizational decision-making using a cognitively realistic Agent model［J］. Journal of Artificial Societies and Social Simulation, 2004, 7(3): 253-258. 
［18］TESTATSION L. Agent-based computational economics: growing economies from the bottom up［J］. Artificial Life, 2002, 8(1): 55-82.
［19］PIERRE M J, CHRISTINE B, GABRIEL L, et al. Bio-inspired mechanisms for artificial self-organized systems［J］. Informatica, 2006, 30(1): 55-62.
?［20］WAGNER G, TULBA F. Agent-oriented modeling and Agent-based simulation［C］//Proceedings of 5th Int Workshop on Agent-Oriented Information Systems(AOIS-2003).［S.l.］: Springer-Verlag, 2003： 57-63.
［21］MILLER J H, PAGE S E. Complex adaptive systems: an introduction to computational models of social life［M］. Princeton, USA: Princeton University Press, 2007： 25-28.
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