Genetic algorithms: hints from biological science

Author

Nie, Xiaosong ; Surkan, Alvin J.

Author_Institution

Dept. of Comput. Sci. & Eng., Nebraska Univ., Lincoln, NE, USA

fYear

1991

fDate

18-21 Nov 1991

Firstpage

426

Abstract

C.T. Walbridge (Technology Review, vol.92, p.46-53, (1989)) discussed how ideas from evolution theory can be used to help in solving problems often addressed by the traditional symbolic methods of artificial intelligence. Choosing VLSI design as an example, he suggested that a chip chromosome would evolve just as genes evolve and the surviving organisms would mate to produce offspring having the chromosomes for the most efficient chips. These result from a combining of different parts of different chromosomes in the offspring to preserve characteristics derived from their parents. The example of a basic square root computation serves to illustrate how the ideas from evolution theory and biological science can be used in the design of globally more efficient genetic algorithms

Keywords

biology; digital arithmetic; genetic algorithms; neural nets; biological science; chip chromosome; evolution theory; genes; genetic algorithms; square root computation; Algorithm design and analysis; Artificial intelligence; Biological cells; Biology computing; Computer science; Evolution (biology); Genetic algorithms; Organisms; Random number generation; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1991. 1991 IEEE International Joint Conference on

Print_ISBN

0-7803-0227-3

Type

conf

DOI

10.1109/IJCNN.1991.170438

Filename

170438