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.
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