Machine Learning

Lieferzeit: Lieferbar innerhalb 14 Tagen

139,09 

An Artificial Intelligence Approach, Symbolic Computation – Artificial Intelligence

ISBN: 3662124076
ISBN 13: 9783662124079
Herausgeber: R S Michalski/J G Carbonell/T M Mitchell
Verlag: Springer Verlag GmbH
Umfang: xi, 572 S., 25 s/w Illustr., 572 p. 25 illus.
Erscheinungsdatum: 03.10.2013
Auflage: 1/2013
Produktform: Kartoniert
Einband: Kartoniert

With contributions by numerous experts

Artikelnummer: 5649620 Kategorie:

Beschreibung

The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial intelligence, infor mation science, pattern recognition, psychology, education, epistemology, philosophy, and related disciplines. The recent observance of the silver anniversary of artificial intelligence has been heralded by a surge of interest in machine learning-both in building models of human learning and in understanding how machines might be endowed with the ability to learn. This renewed interest has spawned many new research projects and resulted in an increase in related scientific activities. In the summer of 1980, the First Machine Learning Workshop was held at Carnegie-Mellon University in Pittsburgh. In the same year, three consecutive issues of the Inter national Journal of Policy Analysis and Information Systems were specially devoted to machine learning (No. 2, 3 and 4, 1980). In the spring of 1981, a special issue of the SIGART Newsletter No. 76 reviewed current research projects in the field. This book contains tutorial overviews and research papers representative of contemporary trends in the area of machine learning as viewed from an artificial intelligence perspective. As the first available text on this subject, it is intended to fulfill several needs.

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E-Mail: juergen.hartmann@springer.com

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