Algorithmic Learning

For several decades, machine learning has been the province of a few enthusiasts. Like other forms of artificial intelligence, it held great promise and no more. 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. The text presents more than thirty algorithms, together with discussions and comparisons, underlying methods, examples, and exercises. The last chapter summarizes several approaches to learning theory and also discusses representations, 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 seeking an up-to-date review of this changing field.