• DocumentCode
    1343415
  • Title

    Evolving computer programs without subtree crossover

  • Author

    Chellapilla, Kumar

  • Author_Institution
    Dept. of Electr. & Comput. Eng., California Univ., San Diego, CA, USA
  • Volume
    1
  • Issue
    3
  • fYear
    1997
  • fDate
    9/1/1997 12:00:00 AM
  • Firstpage
    209
  • Lastpage
    216
  • Abstract
    An evolutionary programming procedure is used for optimizing computer programs in the form of symbolic expressions. Six tree mutation operators are proposed. Recombination operators such as crossover are not included. The viability and efficiency of the method is extensively investigated on a set of well-studied problems. The evidence indicates that the technique is not only viable but is indeed capable of evolving good computer programs. The results compare well with other evolutionary methods that rely on crossover to solve the same problems
  • Keywords
    automatic programming; genetic algorithms; programming theory; search problems; computer programs optimisation; evolutionary programming procedure; symbolic expressions; tree mutation operators; Computational modeling; Computer simulation; Engines; Genetic algorithms; Genetic mutations; Genetic programming; Machine learning; Simulated annealing;
  • fLanguage
    English
  • Journal_Title
    Evolutionary Computation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1089-778X
  • Type

    jour

  • DOI
    10.1109/4235.661552
  • Filename
    661552