Title :
A new approach to genetic based machine learning for efficient improvement of local portions of chromosomes
Author :
Furuhashi, T. ; Miyata, Y. ; 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 this new approach the Nagoya approach. The Nagoya approach is efficient in improving local portions of chromosomes. A simulation of simple computer graphics using the new approach is done. An obstacle avoidance of mobile robot is also simulated using the Nagoya approach and complex fuzzy rules are found.<>
Keywords :
adaptive systems; cellular biophysics; genetic algorithms; learning (artificial intelligence); mobile robots; path planning; Nagoya approach; chromosomes; complex fuzzy rules; computer graphics; genetic based machine learning; imaginary evolution mechanism; mobile robot path planning; obstacle avoidance; Adaptive systems; Biological cells; Computational modeling; Computer graphics; Computer simulation; Genetic algorithms; Hardware; Machine learning; Mobile robots; Production systems;
Conference_Titel :
Emerging Technologies and Factory Automation, 1994. ETFA '94., IEEE Symposium on
Conference_Location :
Tokyo, Japan
Print_ISBN :
0-7803-2114-6
DOI :
10.1109/ETFA.1994.401976
