An agent-based evolutionary approach is proposed to extract interpretable rule-based knowledge. In the multiagent system, each fuzzy set agent autonomously determines its own fuzzy sets information, such as the number and distribution of the fuzzy sets. It can further consider the interpretability of fuzzy systems with the aid of hierarchical chromosome formulation and interpretability-based regulation method. Based on the obtained fuzzy sets, the Pittsburgh-style approach is applied to extract fuzzy rules that take both the accuracy and interpretability of fuzzy systems into consideration. In addition, the fuzzy set agents can cooperate with each other to exchange their fuzzy sets information and generate offspring agents. The parent agents and their offspring compete with each other through the arbitrator agent based on the criteria associated with the accuracy and interpretability to allow them to remain competitive enough to move into the next population. The performance with emphasis upon both the accuracy and interpretability based on the agent-based evolutionary approach is studied through some benchmark problems reported in the literature. Simulation results show that the proposed approach can achieve a good tradeoff between the accuracy and interpretability of fuzzy systems.
|Number of pages||13|
|Journal||IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews|
|Early online date||25 Apr 2005|
|Publication status||Published - May 2005|
Bibliographical noteFunding Information:
This work was supported in part by the City University of Hong Kong under Strategic Grant #7001416 and in part by the Key Natural Science Foundation of Zhejiang Province #ZD0107. This paper was recommended by Guest Editor Y. Jin. H. Wang is with the Department of Computer Science, City University of Hong Kong, Hong Kong. He is also with the College of Electrical Engineering, Zhejiang University, Hong Kong (e-mail: firstname.lastname@example.org). S. Kwong is with the Department of Computer Science, City University of Hong Kong, Hong Kong (e-mail: email@example.com). Y. Jin is with Honda Research Institute Europe, Offenbach/Main 63073, Germany (e-mail: firstname.lastname@example.org). W. Wei is with the College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China (e-mail: email@example.com). K.-F. Man is with the Department of Electronic Engineering, City University of Hong Kong, Hong Kong (e-mail: firstname.lastname@example.org).
- Hierarchical chromosome formulation
- Interpretability and accuracy
- Multiagent system
- Multiobjective decision making