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Algorithmic Learning (Graduate Texts in Computer Science, No 2)

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Back cover blurb: "...a thorough introduction to all aspects of the subject. The text presents more than thirty algorithms, together with discussions and comparison, underlying methods, examples, and exercises. The last chapter summarizes several approaches to learning theory and also discusses represntations, bias, and other topics of current research. This book will be valuable both as a study text for students and as a reference for practitioners...."

From a Review: "This is the kind of book which will make many academics consider developing a new course...ten out of ten to Hutchinson for writing a comprehensive and lively book." -- Igor Aleksander

TABLE OF CONTENTS
1. Characteristics of Learning Algorithms
2. Some Basic Ideas
3. Learning Algorithms With Numeric Input
4. Association and Neural Networks
5. Clustering and Correlation
6. Pattern Matching and Generalization
7. Learning in Rule-Based Systems
8. Further Developments

9 page Bibliography.