Systems that learn : an introduction to learning theory for cognitive and computer scientists / Daniel N. Osherson, Michael Stob, Scott Weinstein.
By: Osherson, Daniel N [author.]
.
Contributor(s): Stob, Michael | Weinstein, Scott | IEEE Xplore (Online Service) [distributor.] | MIT Press [publisher.].
Material type: 
BookSeries: Learning, development, and conceptual change: Publisher: Cambridge, Massachusetts : MIT Press, c1986Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [1990]Description: 1 PDF (ix, 205 pages).Content type: text Media type: electronic Carrier type: online resourceISBN: 9780262256742.Subject(s): Learning -- Mathematical models | Learning, Psychology of | Human information processing -- Mathematical modelsGenre/Form: Electronic books.Additional physical formats: Print version: No titleDDC classification: 153.1/5/015113 Online resources: Abstract with links to resource Also available in print.Summary: 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.Daniel N. Osherson and Scott Weinstein are at MIT, and Michael Stob at Calvin College.
"A Bradford book."
Includes indexes.
Includes bibliographical references (p. )[195]-197.
Restricted to subscribers or individual electronic text purchasers.
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.Daniel N. Osherson and Scott Weinstein are at MIT, and Michael Stob at Calvin College.
Also available in print.
Mode of access: World Wide Web
Description based on PDF viewed 12/28/2015.
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