• DocumentCode
    1551533
  • Title

    Symbolic Models and Emergent Models: A Review

  • Author

    Weng, Juyang

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA
  • Volume
    4
  • Issue
    1
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    29
  • Lastpage
    53
  • Abstract
    There exists a large conceptual gap between symbolic models and emergent models for the mind. Many emergent models work on low-level sensory data, while many symbolic models deal with high-level abstract (i.e., action) symbols. There has been relatively little study on intermediate representations, mainly because of a lack of knowledge about how representations fully autonomously emerge inside the closed brain skull, using information from the exposed two ends (the sensory end and the motor end). As reviewed here, this situation is changing. A fundamental challenge for emergent models is abstraction, which symbolic models enjoy through human handcrafting. The term abstract refers to properties disassociated with any particular form. Emergent abstraction seems possible, although the brain appears to never receive a computer symbol (e.g., ASCII code) or produce such a symbol. This paper reviews major agent models with an emphasis on representation. It suggests two different ways to relate symbolic representations with emergent representations: One is based on their categorical definitions. The other considers that a symbolic representation corresponds to a brain´s outside behaviors observed and handcrafted by other outside human observers; but an emergent representation is inside the brain.
  • Keywords
    cognition; knowledge representation; agent model; brain representation; categorical definition; computer symbol; emergent abstraction; emergent model; high-level abstract symbol; human handcrafting; human observer; intermediate representation; low-level sensory data; symbolic model; symbolic representation; Artificial intelligence; Brain models; Computational modeling; Computer architecture; Humans; Robots; Agents; attention; brain architecture; complexity; computer vision; emergent representation; graphic models; mental architecture; neural networks; reasoning; regression; robotics; speech recognition; symbolic representation; text understanding;
  • fLanguage
    English
  • Journal_Title
    Autonomous Mental Development, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1943-0604
  • Type

    jour

  • DOI
    10.1109/TAMD.2011.2159113
  • Filename
    5872008