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
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