Building expert systems on neural architecture

A novel approach has been developed for building a rule-based system on the neural architecture. Under this approach, the knowledge base and the inference engine are mapped into an entity called conceptualization where a node represents a concept and a link represents a relation between two concepts. Inference in the conceptualization involves propagation and combination of activations as well as maximizing information transmission through layers. Learning is based upon a mechanism called back-propagation, which allows proper modification of connection strengths in order to be adapted to the environment. Finally, the validity of this approach has been demonstrated by experiments.<
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