Bruce F. Katz
Previous efforts to integrate Explanation-Based Learning (EBL) and Similarity-Based Learning (SBL) have treated these two methods as distinct interactive processes. In contrast, the synthesis presented here views these techniques as emergent properties of a local associative learning rule operating within a neural network architecture. This architecture consists of an input layer, a layer buffering this input, but subject to descending influence from higher order units in the network, one or more hidden units encoding the previous knowledge of the network and an output decision layer.
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