• DocumentCode
    2767317
  • Title

    GENSOFNN-YAGER: A Novel Hippocampus-like Learning Memory System Realizing Yager Inference

  • Author

    Oentaryo, Richard J. ; Pasquier, Michel

  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    705
  • Lastpage
    712
  • Abstract
    Recent advances in cognitive neuroscience have revealed the role of hippocampal region as a mediator for explicit memory, which is crucial for human cognitive processes and for developing machine intelligence. This paper presents the novel Generic Self-organizing Fuzzy Neural Network realizing Yager inference (GENSOFNN-YAGER) that is built specifically to model the functional aspects of hippocampus as explicit memory and to emulate human decision making abilities. The main feature of the Yager inference is that, when the input matches the rule antecedent exactly, the resultant output matches the consequent exactly, in a way similar to that of human reasoning. The presented experimental results show the effectiveness of the proposed system.
  • Keywords
    cognitive systems; decision making; fuzzy neural nets; inference mechanisms; self-organising feature maps; Yager inference; generic self-organizing fuzzy neural network; hippocampus-like learning memory system; human cognitive processes; human decision making; human reasoning; neuroscience; Biological neural networks; Decision making; Decision support systems; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Hippocampus; Humans; Impedance matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246753
  • Filename
    1716164