A quantitative analysis of evolvability for an evolutionary fuzzy logic controller

Seung Ik Lee, Sung Bae Cho

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)369-385
Number of pages17
JournalIntegrated Computer-Aided Engineering
Issue number4
Publication statusPublished - 2003

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Artificial Intelligence


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