• DocumentCode
    2459927
  • Title

    Why Simulation-Based Approachs with Combined Fitness are a Good Approach for Mining Spaces of Turing-equivalent Functions

  • Author

    Teytaud, Olivier

  • Author_Institution
    É quipe TAO (INRIA Futurs), LRI, UMR 8623 (CNRS - Université Paris-Sud), Bat. 490, Université Paris Sud, 91405 Orsay CEDEX, France, olivier.teytaud@lri.fr
  • fYear
    2006
  • fDate
    16-21 July 2006
  • Firstpage
    283
  • Lastpage
    290
  • Abstract
    We show negative results about the automatic generation of programs within bounded-time. Combining recursion theory and statistics, we contrast these negative results with positive computability results for iterative approachs like genetic programming, provided that the fitness combines e.g. fastness and size. We then show that simulation-based approachs (approachs evaluating only by simulation the quality of programs) like GP are not too far from the minimal time required for evaluating these combined fitnesses.
  • Keywords
    Computational efficiency; Computational modeling; Convergence; Costs; Equations; Genetic programming; Iterative algorithms; Iterative methods; Statistical learning; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
  • Print_ISBN
    0-7803-9487-9
  • Type

    conf

  • DOI
    10.1109/CEC.2006.1688320
  • Filename
    1688320