Translating neural networks into rule-based expert systems

Summary form only given. Attention is given to Knowledgetron, a novel, domain-independent system dedicated to automatically translating the knowledge of an artificial neural network which has been trained to classify the data correctly using backpropagation into a set of if-then rules. Knowledgetron is able to generate rules from an adapted net in an efficient way. Learning parameters of the net that critically influence the system behavior are identified. The system is able to deal with both single-layer and multilayer networks, and can learn both confirming and disconfirming rules. The tractability of the learning algorithm of Knowledgetron was shown analytically. Empirically, Knowledgetron was demonstrated in the domain of wind shear detection by infrared sensors with success