• DocumentCode
    2409822
  • Title

    Using a distance metric on genetic programs to understand genetic operators

  • Author

    O´Reilly, U.-M.

  • Author_Institution
    Artificial Intelligence Lab., MIT, Cambridge, MA
  • Volume
    5
  • fYear
    1997
  • fDate
    12-15 Oct 1997
  • Firstpage
    4092
  • Abstract
    I describe a distance metric called “edit” distance which quantifies the syntactic difference between two genetic programs. In the context of one specific problem, the 6 bit multiplexor, I use the metric to analyze the amount of new material introduced by different crossover operators, the difference among the best individuals of a population and the difference among the best individuals and the rest of the population. The relationships between these data and run performance are imprecise but they are sufficiently interesting to encourage further investigation into the use of edit distance
  • Keywords
    genetic algorithms; search problems; software metrics; software performance evaluation; trees (mathematics); best individuals; crossover operators; distance metric; edit distance; genetic operators; genetic programs; multiplexor; population; run performance; search; syntactic difference; trees; Artificial intelligence; Genetic programming; Information analysis; Performance analysis; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4053-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1997.637337
  • Filename
    637337