Automated Knowledge Acquisition

This tutorial provides clear explanations of techniques for automated knowledge acquisition. The techniques covered include: decision tree methods, progressive rule generation, explanation-based learning, artificial neural networks, and genetic algorithm approaches. The book is suitable for both advanced undergraduate and graduate students and computer professionals.

This tutorial provides clear explanations of techniques for automated knowledge acquisition. Covers topics such as induction algorithms using decision trees; induction algorithms using progressive rule generation; sub-symbolic learning methods, artificial neural networks; other machine learning paradigms; theoretical considerations; the extraction of rules and concepts using a single-layered Hebbian neural network; BRAINNE - automated knowledge acquisition using multi-layered neural network; and BRAINNE in the real world. For computer professionals who wish to gain a good understanding of automated knowledge acquisition techniques.