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

Alan Hutchinson (Author)

Book Description

Series: Graduate Texts in Computer Science, No 2 | Publication Date: June 9, 1994

For the last few decades, machine learning has been the province of a few enthusiasts. Like other forms of artificial intelligence, it held great promise but remained largely undeveloped. This situation is changing. We are now familiar with a wide range of algorithms, and a theory outlining which algorithm will suit which purpose is beginning to emerge. The science of machine learning is coming of age. Algorithmic Learning provides a thorough introduction to all aspects of the subject. It presents more than 30 algorithms as well as examples, exercises, and comparisons between underlying methods. The last chapter summarizes several approaches to learning theory and discusses representations, bias, and other topics of current research. The book will be invaluable to students, researchers, and professionals in artificial intelligence, neural computing, and cognitive science seeking an up-to-date review of this exciting and dynamic field.

Editorial Reviews

Review

`Hutchinson writes in a compelling and well-organised fashion - it is quite difficult not to be seduced by his enthusiasm. So ten out of ten to Hutchinson for writing a comprehensive and lively book.' Times Higher Education Supplement

`The book is comprehensive and well-written.' J W Grzymala-Busse, Zbl Math 836/96

About the Author

Alan Hutchinson, Lecturer, Department of Computer Science, King's College, London.

Product Details

• Paperback: 464 pages
• Publisher: Oxford University Press, USA (June 9, 1994)
• Language: English
• ISBN-10: 0198538480
• ISBN-13: 978-0198538486
• Product Dimensions: 9.2 x 6.1 x 1.1 inches
• Shipping Weight: 1.7 pounds
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #5,096,938 in Books (See Top 100 in Books)

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5.0 out of 5 stars About This Book, August 30, 2008

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This review is from: Algorithmic Learning (Graduate Texts in Computer Science, No 2) (Paperback)

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.