• DocumentCode
    1749074
  • Title

    Recurrent neural networks and symbol grounding

  • Author

    Spiegel, Rainer ; McLaren, IPL

  • Author_Institution
    Dept. of Exp. Psychol., Cambridge Univ., UK
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    320
  • Abstract
    It is demonstrated that a recurrent neural network relying on statistics alone is able to differentiate between the classical Aristotelian categories odd and even number. This finding overlaps with the associative part of the hybrid associative/cognitive learning system in humans who sometimes differentiate between both categories unknowingly, i.e. without explicit rules
  • Keywords
    psychology; recurrent neural nets; classical Aristotelian categories; even number; humans; hybrid associative/cognitive learning system; odd number; recurrent neural networks; symbol grounding; Cognition; Cognitive science; Grounding; Humans; Knowledge based systems; Learning systems; Psychology; Recurrent neural networks; Statistics; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.939039
  • Filename
    939039