Systems That Learn: An Introduction to Learning Theory for Cognitive and Computer Scientists

by Daniel N. Osherson, Michael Stob, Scott Weinstein

Overview

A mathematical framework for the study of learning in a variety of domains.

Systems That Learn presents a mathematical framework for the study of learning in a variety of domains. It provides the basic concepts and techniques of learning theory as well as a comprehensive account of what is currently known about a variety of learning paradigms.

Product Details

ISBN-13:	9780262650243
Publisher:	MIT Press
Publication date:	03/14/1990
Series:	Learning, Development, and Conceptual Change
Pages:	205
Product dimensions:	6.00(w) x 9.00(h) x (d)
Age Range:	18 Years

About the Author

Daniel N. Osherson is at MIT.


Michael Stob at Calvin College.


Scott Weinstein is at MIT.

What People are Saying About This

Contemporary Psychology

Systems That Learn is a book that has much to offer... Osherson, Stob, and Weinstein provide an interesting contrast to most of the learning work done either in psychology or artificial intelligence.

Endorsement

This is highly original and interesting research. Systems That Learn is an important addition to human knowledge and an incipient classic.

—Steven Pinker, MIT

From the Publisher

Systems That Learn is a book that has much to offer... Osherson, Stob, and Weinstein provide an interesting contrast to most of the learning work done either in psychology or artificial intelligence.

—Contemporary Psychology

This is highly original and interesting research. Systems That Learn is an important addition to human knowledge and an incipient classic.

—Steven Pinker, MIT

Steven Pinker

This is highly original and interesting research. Systems That Learn is an important addition to human knowledge and an incipient classic.