• DocumentCode
    3269305
  • Title

    Choosing Best Fitness Function with Reinforcement Learning

  • Author

    Afanasyeva, Arina ; Buzdalov, Maxim

  • Author_Institution
    Nat. Res. Univ. of Inf. Technol., Mech. & Opt., St. Petersburg, Russia
  • Volume
    2
  • fYear
    2011
  • fDate
    18-21 Dec. 2011
  • Firstpage
    354
  • Lastpage
    357
  • Abstract
    This paper describes an optimization problem with one target function to be optimized and several supporting functions that can be used to speed up the optimization process. A method based on reinforcement learning is proposed for choosing a good supporting function during optimization using genetic algorithm. Results of applying this method to a model problem are shown.
  • Keywords
    genetic algorithms; learning (artificial intelligence); mathematics computing; fitness function; genetic algorithm; optimization problem; reinforcement learning; Computational modeling; Genetic algorithms; Heuristic algorithms; Learning; Machine learning; Optimization; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    978-1-4577-2134-2
  • Type

    conf

  • DOI
    10.1109/ICMLA.2011.163
  • Filename
    6147704
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3269305