DocumentCode :
2065989
Title :
A hybrid approach for knowledge representation and reasoning
Author :
Schwinn, Johannes
Author_Institution :
IMAT-MMS, Kassel Univ., Germany
fYear :
1993
fDate :
24-26 Nov 1993
Firstpage :
214
Lastpage :
215
Abstract :
Symbolic knowledge-based systems as well as neural networks offer several advantages, but suffer from several disadvantages if they are used as isolated systems. In consideration of this fact the main idea is to propose an architecture which is capable of handling both paradigms in one system. In the suggested approach neural networks are treated as an additional virtual symbolic knowledge representation and reasoning mechanism which is handled by a meta interpreter just like other symbolic forms of representation, offered by the symbol system. From this point of view the described system offers an unified view to hybrid problem solving
Keywords :
inference mechanisms; knowledge representation; neural nets; symbol manipulation; hybrid approach; hybrid problem solving; knowledge representation; meta interpreter; neural networks; reasoning; symbolic knowledge-based systems; virtual symbolic knowledge representation; Expert systems; Knowledge based systems; Knowledge representation; Laboratories; Man machine systems; Neural networks; Object oriented modeling; Problem-solving;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1993. Proceedings., First New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-4260-2
Type :
conf
DOI :
10.1109/ANNES.1993.323041
Filename :
323041
Link To Document :
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