• DocumentCode
    345647
  • Title

    Evolution, emergence, semiosis: components of the model for intelligent system

  • Author

    Meystel, A.

  • Author_Institution
    Drexel Univ., Philadelphia, PA, USA
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    452
  • Lastpage
    454
  • Abstract
    The discussion of intelligent system usually starts with issues of defining intelligence as a set of skills, but always ends with specifying the mechanisms of learning. It is important to address the issue of differences and similarities between the techniques of computational/control learning processes (very similar to the processes of semiosis) and biological learning including evolution of species where the resemblance with semiosis is less obvious. We would like to attract attention to the theory of multilevel processes of evolution which are interpreted in this paper as multiresolutional processes of evolution. Novel explanations are preposed for numerous paradoxes known in the area of computational and biological learning including evolution of species. The direct linkage is demonstrated of learning processes and the development of decision-making mechanisms for single and multiple agents
  • Keywords
    evolution (biological); learning (artificial intelligence); learning systems; biological learning; computational learning; control learning; emergence; intelligent system; learning; multilevel evolution processes; multiresolutional evolution processes; semiosis; Actuators; Biological control systems; Biological system modeling; Biology computing; Computational intelligence; Control systems; Decision making; Evolution (biology); Hardware; Intelligent systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control/Intelligent Systems and Semiotics, 1999. Proceedings of the 1999 IEEE International Symposium on
  • Conference_Location
    Cambridge, MA
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-5665-9
  • Type

    conf

  • DOI
    10.1109/ISIC.1999.796697
  • Filename
    796697