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
Link To Document :
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