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

fYear

1994

fDate

6-10 Nov. 1994

Firstpage

458

Lastpage

465

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Technologies and Factory Automation, 1994. ETFA '94., IEEE Symposium on

Conference_Location

Tokyo, Japan

Print_ISBN

0-7803-2114-6

Type

conf

DOI

10.1109/ETFA.1994.401976

Filename

401976

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2772745