Learning Machines: Foundations of Trainable Pattern-Classifying Systems

by Nils J. Nilsson

A learning machine, broadly defined, is any device whose actions are influenced by past experiences. The present work deals with the theory of a subclass of learning machines, those which can be trained to recognize patterns. Some well known examples of trainable pattern-classifying systems the PERCEPRON and MADALINE and MINOS networks.

137 pages, Hardcover

Published January 1, 1965

About the author

Nils J. Nilsson is Kumagai Professor of Engineering, Emeritus, in the Department of Computer Science at Stanford University. He is the author of The Quest for Artificial Intelligence: A History of Ideas and Achievements and other books. He lives in Oregon.