• DocumentCode
    3303653
  • Title

    Mutation buffering capabilities of the hypernetwork model

  • Author

    Segovia-Juárez, José L. ; Colombano, Silvano

  • Author_Institution
    Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    7
  • Lastpage
    13
  • Abstract
    The hypernetwork is a molecular interaction-based model that has learning capabilities. The adaptive algorithm randomly changes the molecular structures and selects the best individual. Experiments with the hypernetwork show the importance for evolution of the mutation buffering capabilities of the system. Mutation buffering allows the system to improve its search for peaks in the fitness landscape
  • Keywords
    biocomputing; learning (artificial intelligence); adaptive algorithm; fitness landscape; hypernetwork model; learning; molecular interaction-based model; mutation buffering; mutation buffering capabilities; Biological system modeling; Biological systems; Biology computing; Computer science; Distributed computing; Evolution (biology); Genetic mutations; Hardware; Organisms; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolvable Hardware, 2001. Proceedings. The Third NASA/DoD Workshop on
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    0-7695-1180-5
  • Type

    conf

  • DOI
    10.1109/EH.2001.937941
  • Filename
    937941