A quantitative analysis of evolvability for an evolutionary fuzzy logic controller

Article type: Research Article

Authors: Lee, Seung-Ik^{a; b; *} | Cho, Sung-Bae^b

Affiliations: [a] ATR International, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan. Tel.: +81 774 95 2687; Fax: +81 774 95 2647 | [b] Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, South Korea. Tel.: +82 2123 2720; Fax: +82 365 2579; E-mail: [email protected], [email protected]

Correspondence: [*] Corresponding author.

Abstract: This paper presents a quantitative analysis of evolvability with evolutionary activity statistics in an evolutionary fuzzy system. In general, one can estimate the performance of an evolved fuzzy controller by its fitness. However, it is difficult to explain how its fitness or adaptability has been obtained. Evolutionary activity is used to measure the evolvability of fuzzy rules and explain why salient rules have higher evolvability. A genetic algorithm is used to construct a fuzzy logic controller for a mobile robot in simulation environments. The quantitative analysis shows that sufficient evolvability is maintained during the evolution and that it contributes to the construction of the optimal controller.

DOI: 10.3233/ICA-2003-10407

Journal: Integrated Computer-Aided Engineering, vol. 10, no. 4, pp. 369-385, 2003