Knowledge Refinement Using Knowledge Acquisition and Machine Learning Methods

APT system integrates Machine Learning (ML) and Knowledge Acquisition (KA) methods in the same framework. Both kinds of methods closely cooperate to concur in the same purpose: the acquisition, validation and maintenance of problem-solving knowledge. The methods are based on the same assumption: knowledge acquisition and learning are done through experimentation, classification and comparison of concrete cases. This paper details APT's mechanisms and shows through examples and applications how APT underlying principles allow various methods to fruitfully collaborate.

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