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9780262650243

Systems That Learn

by ; ;
  • ISBN13:

    9780262650243

  • ISBN10:

    026265024X

  • Edition: Reprint
  • Format: Paperback
  • Copyright: 1990-03-14
  • Publisher: Bradford Books

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Summary

Systems That Learnpresents 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.

Table of Contents

Series Forewordp. xi
Prefacep. xiii
Acknowledgmentsp. xv
How to Use This Bookp. xvii
Introductionp. 1
Identification
Fundamentals of Learning Theoryp. 7
Central Theorems on Identificationp. 25
Learning Theory and Natural Languagep. 34
Identification Generalized
Strategiesp. 45
Environmentsp. 96
Criteria of Learningp. 119
Exact Learningp. 152
Other Paradigms Of Learning
Efficient Learningp. 167
Sufficient Input for Learningp. 178
Topological Perspective on Learningp. 182
Bibliographyp. 195
List of Symbolsp. 198
Name Indexp. 201
Subject Indexp. 203
Table of Contents provided by Publisher. All Rights Reserved.

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