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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2
A General Framework for Symbol and Rule Extraction in Neural Networks
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
ASCII Text
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B. Apolloni, C. Orovas, J. Taylor, W. Fellenz, Stan Gielen, Machiel Westerdijk, "A General Framework for Symbol and Rule Extraction in Neural Networks," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 2, pp. 2087, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000.
 
 
BibTex
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@article{ 10.1109/IJCNN.2000.857879,
author = {B. Apolloni and C. Orovas and J. Taylor and W. Fellenz and Stan Gielen and Machiel Westerdijk},
title = {A General Framework for Symbol and Rule Extraction in Neural Networks},
journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
volume = {2},
year = {2000},
issn = {1098-7576},
pages = {2087},
doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857879},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
TI - A General Framework for Symbol and Rule Extraction in Neural Networks
SN - 1098-7576
SP
EP
A1 - B. Apolloni,
A1 - C. Orovas,
A1 - J. Taylor,
A1 - W. Fellenz,
A1 - Stan Gielen,
A1 - Machiel Westerdijk,
PY - 2000
VL - 2
JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
ER -
 
B. Apolloni, University of Milan
C. Orovas, University of Milan
J. Taylor, King's College London
W. Fellenz, King's College London
Stan Gielen, University of Nijmegen
Machiel Westerdijk, University of Nijmegen
We split the rule extraction task in to a sub-symbolic and a symbolic phase and present a set of neural networks for filling the former. Under the two general commitments of: i) having a learning algorithm that is sensitive to feedback signals coming from the latter phase, and ii) extracting Boolean variables whose meaning is determined by the further symbolic processing, we introduce three unsupervised learning algorithms and show related numerical examples for a multilayer perceptron, recurrent neural networks, and a specially devised vector quantizer.
Citation:
B. Apolloni, C. Orovas, J. Taylor, W. Fellenz, Stan Gielen, Machiel Westerdijk, "A General Framework for Symbol and Rule Extraction in Neural Networks," ijcnn, vol. 2, pp.2087, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000
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