An efficient finding of fuzzy rules using a new approach to genetic based machine learning

19 November 2002

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 2, 715-722
https://doi.org/10.1109/fuzzy.1995.409762

Abstract

This paper presents a new approach to genetic based machine learning (GBML). The new approach is based on an imaginary mechanism of evolution. The authors call the new approach Nagoya approach. The Nagoya approach is efficient in finding complex rules. An obstacle avoidance of mobile robot is simulated using the new GBML, and complex fuzzy rules are found.<>

Keywords

MACHINE LEARNING
BIOLOGICAL CELLS
MOBILE ROBOTS
PRODUCTION SYSTEMS
GENETIC ALGORITHMS
ADAPTIVE SYSTEMS
HARDWARE
FIRES
TESTING
GENETIC MUTATIONS

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COGNITIVE SYSTEMS BASED ON ADAPTIVE ALGORITHMS11Research reported in this paper was supported in part by the National Science Foundation under grant DCR 71-01997 and by the Horace H. Rackham School of Graduate Studies under grant 387156.
Published by Elsevier ,1978