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Systems that learn : an introduction to learning theory for cognitive and computer scientists / Daniel N. Osherson, Michael Stob, Scott Weinstein.
- Format:
- Book
- Author/Creator:
- Osherson, Daniel N.
- Series:
- Learning, development, and conceptual change
- The MIT Press series in learning, development, and conceptual change
- Language:
- English
- Subjects (All):
- Learning, Psychology of.
- Learning--Mathematical models.
- Learning.
- Human information processing--Mathematical models.
- Human information processing.
- Physical Description:
- 1 online resource (ix, 205 pages)
- Edition:
- 1st ed.
- Place of Publication:
- Cambridge, Mass. : MIT Press, c1986.
- Summary:
- A mathematical framework for the study of learning in a variety of domains.
- Contents:
- Intro
- Series Foreword
- Preface
- Acknowledgments
- How to Use This Book
- 1. Fundamentals of Learning Theory
- 2. Central Theorems on Identification
- 3. Learning Theory and Natural Language
- 4. Strategies
- 5. Environments
- 6. Criteria of Learning
- 7. Exact Learning
- 8. Efficient Learning
- 9. Sufficient Input for Learning
- 10. Topological Perspective on Learning
- Bibliography
- List of Symbols
- Name Index
- Subject Index.
- Notes:
- "A Bradford book."
- Includes bibliography (p. [195]-197) and indexes.
- Description based on publisher supplied metadata and other sources.
- OCLC:
- 1129210521
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