DocumentCode
2301822
Title
Studies on the effect of non-coding segments on the genetic algorithm
Author
Wu, Annie S. ; Lindsay, Robert K. ; Smith, Michael D.
Author_Institution
Artificial Intelligence Lab., Michigan Univ., Ann Arbor, MI, USA
fYear
1994
fDate
6-9 Nov 1994
Firstpage
744
Lastpage
747
Abstract
We study a specific aspect of the genetic algorithm (GA): the effect of non-coding segments on GA performance. Non-coding segments are segments of bits in an individual that provide no contribution, positive or negative, to the fitness of that individual. Previous research on non-coding segments suggests that including these structures in the GA population may improve GA performance. As a first step in our research, we tested our program on some of the same problems as the previous studies. This paper compares our results with the previous results and discusses the significance of the similarities and differences
Keywords
genetic algorithms; genetic algorithm; noncoding segments; performance; Artificial intelligence; DNA; Genetic algorithms; Measurement; Organisms; Problem-solving; Proteins; RNA; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location
New Orleans, LA
Print_ISBN
0-8186-6785-0
Type
conf
DOI
10.1109/TAI.1994.346411
Filename
346411
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