• DocumentCode
    807923
  • Title

    The Role Of The Lamarck Hypothesis In The Grammatical Evolution Guided By Reinforcement

  • Author

    Mingo, J.M. ; Aler, R.

  • Author_Institution
    Dept. de Inf., Univ. Carlos III de Madrid, Leganes
  • Volume
    6
  • Issue
    6
  • fYear
    2008
  • Firstpage
    500
  • Lastpage
    504
  • Abstract
    Grammatical evolution is an evolutionary algorithm able to develop programs in any language, defined by a grammar. The evolutionary process may be improved if we let the individuals learn during their lifetime. with this aim, the grammatical evolution guided by reinforcement, an algorithm which merges evolution and learning, was created. Grammatical evolution guided by reinforcement uses a Lamarckian mechanism for replacing the original genotypes when a successful learning has occurred. This paper explores the role of the Lamarckian hypothesis. At the same time, grammatical evolution guided by reinforcement is tested in a new domain: autonomous navigation in a Kephera robot simulation.
  • Keywords
    evolutionary computation; grammars; learning (artificial intelligence); IWPAAMS2007-02; Kephera robot simulation; Lamarckian hypothesis; evolutionary algorithm; grammatical evolution; reinforcement learning; Bioinformatics; Biology computing; Evolutionary computation; Genomics; Learning; Navigation; Robots; Surges; Testing; Grammatical Evolution; Lamarck Effect; Reinforcement Learning;
  • fLanguage
    English
  • Journal_Title
    Latin America Transactions, IEEE (Revista IEEE America Latina)
  • Publisher
    ieee
  • ISSN
    1548-0992
  • Type

    jour

  • DOI
    10.1109/TLA.2008.4908181
  • Filename
    4908181