• DocumentCode
    2958547
  • Title

    Towards A Novel Integrated Neuro-Cognitive Architecture (INCA)

  • Author

    Oentaryo, Richard J. ; Pasquier, Michel

  • Author_Institution
    Centre for Comput. Intell., Nanyang Technol. Univ., Singapore
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    1902
  • Lastpage
    1909
  • Abstract
    Artificial intelligence research is now flourishing which aims at achieving general, human-level intelligence. Accordingly, cognitive architectures are increasingly employed as blueprints for building intelligent agents to be endowed with various perceptive and cognitive abilities. This paper presents a novel integrated neuro-cognitive architecture (INCA) which emulate the putative functional aspects of various salient brain sub-systems via a learning memory modeling approach. The strength of INCA lies in self-organizing connectionist learning to induce high-level symbolic knowledge autonomously, and support for meta-cognitive functions. Its overall operations are governed by its consolidation and inference cycles, which posit a human-plausible way for forming and exploiting knowledge.
  • Keywords
    artificial intelligence; cognitive systems; inference mechanisms; learning systems; neural net architecture; artificial intelligence research; inference cycles; integrated neuro-cognitive architecture; learning memory modeling approach; meta-cognitive functions; salient brain subsystems; self-organizing connectionist learning; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4634058
  • Filename
    4634058