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
Link To Document :
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