Expert discovery and knowledge mining in complex multi-agent systems Article First Online: 26 May 2007 DOI:
Cite this article as: Zhang, M., Tang, X., Bai, Q. et al. J. Syst. Sci. Syst. Eng. (2007) 16: 222. doi:10.1007/s11518-007-5043-9 Abstract
Complex problem solving requires diverse expertise and multiple techniques. In order to solve such problems, complex multi-agent systems that include both of human experts and autonomous agents are required in many application domains. Most complex multi-agent systems work in open domains and include various heterogeneous agents. Due to the heterogeneity of agents and dynamic features of working environments, expertise and capabilities of agents might not be well estimated and presented in these systems. Therefore, how to discover useful knowledge from human and autonomous experts, make more accurate estimation for experts’ capabilities and find out suitable expert(s) to solve incoming problems (“Expert Mining”) are important research issues in the area of multi-agent system. In this paper, we introduce an ontology-based approach for knowledge and expert mining in hybrid multi-agent systems. In this research, ontologies are hired to describe knowledge of the system. Knowledge and expert mining processes are executed as the system handles incoming problems. In this approach, we embed more self-learning and self-adjusting abilities in multi-agent systems, so as to help in discovering knowledge of heterogeneous experts of multi-agent systems.
This work was supported by a Scientific Cooperation Program between Chinese Academy of Sciences and Australian Academy of Science in 2005–2006, and National Natural Sciences Foundation of Science (Grant No. 70571078 & 70221001). The original version was presented at the conference of KSSS06.
Minjie Zhang received her Bachelor of Science (in Computer Science) from Fudan University, China in 1982, and her PhD degree from the University of New England, Australia in 1996. Currently she is an associate professor in the School of Computer Science and Software Engineering at University of Wollongong, Australia. She was a co-chair for the First Pacific Rim International Workshop on Electronic Commerce in 2006, and an organization chair, for the International Workshop on Rational, Robust, and Secure Negotiation Mechanisms in Multi-Agent Systems in 2005, 2006 and 2007 and a tutorial chair of the International Conference on Complex Open Distributed Systems in 2007. She is a member of editorial board of System and Information Sciences Notes and the International Journal of Knowledge and Systems Sciences. Dr Minjie Zhang is an active researcher and published over ninety research papers. She is the chief investigator for more than 10 different research grants including an ARC (Australia Research Council) Discovery grant and an ARC International Linkage Grant. She is a member of IEEE and the International Association of Computer and Their Applications. Her research interests include multi-agent systems, distributed information retrieval, agent-based modeling and simulation, and data mining and knowledge discovery. Xijin Tang acquired her bachelor, master and doctoral degrees in 1989, 1992, and 1995 respectively. Now she is an associate professor in Key Laboratory of Management, Decision-making and Information Systems, Chinese Academy of Sciences. She has been visited Georgia Institute of Technology as research associate during 1998–1999 and Japan Advanced Institute of Science and Technology as a visiting associate professor of “Fujitsu Chair for Science of Complex Systems” during 2000–2001. She has engaged in research on decision support systems and system methodologies, and developed a variety of computerized support systems for water resources management, comprehensive evaluation on commercial information systems, naval weapon system evaluation, etc. during 1992–1998 and devoted to a major NSFC project on meta-synthesis research during 1999–2004. Her current interests include knowledge science, complex system modeling, social network analysis, creativity and decision support systems, etc. which aim to provide effective and intensive knowledge support for unstructured problem solving. Recently she has published two books on meta-synthesis system and the oriental Wu-li Shi-li Ren-li system approach. She has organized 7 international workshops related to meta-synthesis and knowledge science since 2001. She is a council member of Systems Engineering Society of China and of the International Society for Knowledge and Systems Sciences. Quan Bai received his bachelor degree in 2001 from Tianjin University, China, and acquired his Ph.D degree from the University of Wollongong, Australia in 2007. Currently, he is a research fellow in the School of Computer Science and Software Engineering at the University of Wollongong. He has involved in three research projects and published more than fifteen research papers during the period of his PhD study. Dr Quan Bai’s research interests include multi-agent coordination, agent based simulation and modeling, data mining and social network analysis. Jifa Gu, Ph.D., a Professor in Institute of Systems Science, Academy of Mathematics and Systems Sciences, CAS, Beijing, China, His fields of study includes Operations Research and Systems Science. He is a Vice-president of International Federation for Systems Research, and a Vice-president of International Society of Knowledge and Systems Science. He obtained ten awards from Chinese Academy of Sciences and other state organizations.