• DocumentCode
    889253
  • Title

    Redundancy and computational efficiency in Cartesian genetic programming

  • Author

    Miller, Julian F. ; Smith, Stephen L.

  • Author_Institution
    Dept. of Electron., Univ. of York, Heslington, UK
  • Volume
    10
  • Issue
    2
  • fYear
    2006
  • fDate
    4/1/2006 12:00:00 AM
  • Firstpage
    167
  • Lastpage
    174
  • Abstract
    The graph-based Cartesian genetic programming system has an unusual genotype representation with a number of advantageous properties. It has a form of redundancy whose role has received little attention in the published literature. The representation has genes that can be activated or deactivated by mutation operators during evolution. It has been demonstrated that this "junk" has a useful role and is very beneficial in evolutionary search. The results presented demonstrate the role of mutation and genotype length in the evolvability of the representation. It is found that the most evolvable representations occur when the genotype is extremely large and in which over 95% of the genes are inactive.
  • Keywords
    genetic algorithms; graph theory; search problems; computational efficiency; evolutionary search; evolvable representations; genotype representation; graph-based Cartesian genetic programming; mutation operators; Algorithm design and analysis; Computational efficiency; Computer networks; DNA; Digital circuits; Encoding; Evolutionary computation; Genetic mutations; Genetic programming; Neural networks; Cartesian genetic programming (CGP); code bloat; genetic programming; graph-based representations; introns;
  • fLanguage
    English
  • Journal_Title
    Evolutionary Computation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1089-778X
  • Type

    jour

  • DOI
    10.1109/TEVC.2006.871253
  • Filename
    1613935