Author(s)

P.K. Mogili & A.K. Sunol

Abstract

Automation of the knowledge acquisition process in building knowledge- based systems for process design is addressed through Machine Learning techniques. A hybrid Machine Learning algorithm developed at the Uni- versity of South Florida is presented as a knowledge acquisition tool for developing knowledge-based systems. The learning algorithm addresses the knowledge acquisition problem by developing and maintaining the knowledge base through inductive learning from the examples. The learning algorithm named as Symbolic-Connectionist net (SC- net), overcomes the problems associated with neural and symbolic learn- ing systems by integrating the symbolic information into a neural network representation. The learning system allows for knowledge extraction and background knowledge encoding in the form

Keywords