• DocumentCode
    303339
  • Title

    A genetic algorithm for reinforcement learning

  • Author

    Zhao, Long ; Liu, Zemin

  • Author_Institution
    Beijing Univ. of Posts & Telecommun., China
  • Volume
    2
  • fYear
    1996
  • fDate
    3-6 Jun 1996
  • Firstpage
    1056
  • Abstract
    A main difficulty for applying reinforcement learning methods in practice is the large action space problem. In this paper, by means of the concept of genetic optimization, we have proposed a new reinforcement learning algorithm. Our genetic algorithm for reinforcement learning has solved the large action space problem quite well
  • Keywords
    genetic algorithms; learning (artificial intelligence); neural nets; genetic algorithm; genetic optimization; large action space problem; reinforcement learning; Adaptive control; Computational complexity; Equations; Genetic algorithms; Learning automata; Neural networks; Neurons; Programmable control; State-space methods; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1996., IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-3210-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1996.549044
  • Filename
    549044
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=303339