Machine Learning - An Artifical Intelligence Approach

Michalski, R.S., J. G. Carbonell and T.M. Mitchell:

ISBN 10: 3540132988 / ISBN 13: 9783540132981

Published by Springer Verlag;, 1984

About this Item

572 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 1020. Seller Inventory # 1493042

Bibliographic Details

Title: Machine Learning - An Artifical Intelligence...

Publisher: Springer Verlag;

Publication Date: 1984

Binding: gebundene Ausgabe

Condition: Gut

About this title

Synopsis:

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.

From the Publisher:

No other book covers the concepts and techniques from the various fields in a unified fashion.
Covers very recent subjects such as genetic algorithms, reinforcement learning, and inductive logic programming.
Writing style is clear, explanatory and precise.