A neural network model for learning rule-based systems

Knowledgetron, a novel intelligent system which derives rule-based expert systems from neural networks trained by a special computational model, is described. The knowledge of such neural networks is extracted and represented as production rules. The main consideration is that the generated rule-based system perform as well as the original neural network. The system consists of two coupled components. One is the KTBP trainer, which is applied to a multilayer neural network for learning from the data. The trained neural network is translated into a rule-based system by the second component, the KT translator. The feasibility and validity of Knowledgetron have been demonstrated on both small and large neural networks for practical applications.<
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