• 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