On hybrid connectionist-symbolic models
There are many similarities between grammar systems and artificial neural networks: parallelism, independently working elements (grammars/neurons), communication of the elements, absence of centralized control. On the other hand, there are crucial differences between symbolic and quantitative data p...
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Main Author: | |
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Format: | Article |
Published: |
1997
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Series: | Acta cybernetica
13 No. 2 |
Kulcsszavak: | Számítástechnika, Kibernetika |
Subjects: | |
Online Access: | http://acta.bibl.u-szeged.hu/12584 |
Summary: | There are many similarities between grammar systems and artificial neural networks: parallelism, independently working elements (grammars/neurons), communication of the elements, absence of centralized control. On the other hand, there are crucial differences between symbolic and quantitative data processing. We will try to give a brief overview of the methods of "building bridges" between symbolic and connectionist paradigm and to propose some recent results. After that, we will touch some essential problems, concerning incorporation of accepting/generating grammar systems and neural network models. |
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Physical Description: | 159-172 |
ISSN: | 0324-721X |