Title :
An efficient finding of fuzzy rules using a new approach to genetic based machine learning
Author :
Furuhashi, T. ; Nakaoka, K. ; Uchikawa, Y.
Author_Institution :
Dept. of Inf. Electron., Nagoya Univ., Japan
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 :
fuzzy systems; genetic algorithms; knowledge based systems; knowledge representation; learning systems; mobile robots; path planning; Nagoya approach; complex rules; fuzzy rules; genetic based machine learning; imaginary evolution mechanism; mobile robot; obstacle avoidance; Adaptive systems; Biological cells; Fires; Genetic algorithms; Genetic mutations; Hardware; Machine learning; Mobile robots; Production systems; Testing;
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
DOI :
10.1109/FUZZY.1995.409762
