• DocumentCode
    1636825
  • Title

    Reinforcement learning in steady-state cellular genetic algorithms

  • Author

    Lee, Cin-Young ; Antonsson, Erik K.

  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1793
  • Lastpage
    1797
  • Abstract
    A novel cellular genetic algorithm is developed to address the issues of good mate selection. This is accomplished through reinforcement learning where good mating individuals attract and poor mating individuals repel. Adaptation of good mate choice occurs, thus leading to more efficient search. Results are presented for various test cases
  • Keywords
    genetic algorithms; learning (artificial intelligence); good mate selection; reinforcement learning; search; steady-state cellular genetic algorithms; Computation theory; Computational modeling; Convergence; Genetic algorithms; Learning; Production; Robustness; Steady-state; Testing; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1004514
  • Filename
    1004514
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1636825