Learning And Memory / Edition 1

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This book surveys the entire field of learning and memory. It describes the major approaches to its study and looks at basic assumptions and philosophical underpinnings. Howard integrates work from quite different perspectives into a single framework, and describes peripheral areas not usually mentioned in mainstream books, such as prenatal learning, constraints on knowledge, nonconnectionist machine learning, intelligence and learning, and skills learning. He gives the reader a broad knowledge of what the field is all about, what its parts are and how they interrelate, its major principles and key applications. The primary contribution of this work is the integration of current thinking about learning with the literature and research on memory.

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Editorial Reviews

Surveys and systemizes the major assumptions and basic approaches relating to learning and memory from their philosophical principles through cultural manifestations to derivational aspects; does not consider physiology. Includes topics rare in mainstream books, such as nonconnectionist machine learning, constraints on knowledge, skill learning, prenatal learning, and applications in industrial design and the law. Addressed to practitioners, researchers, and graduate and advanced undergraduate students in psychology or related fields. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780275946418
  • Publisher: ABC-CLIO, Incorporated
  • Publication date: 1/24/1995
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 258
  • Lexile: 1180L (what's this?)
  • Product dimensions: 6.14 (w) x 9.21 (h) x 0.63 (d)

Meet the Author

ROBERT W. HOWARD teaches at the University of Newcastle, Australia.

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Table of Contents

1 The Ability to Learn and Remember 1
2 Learning and Memory in Evolution and in Animals 29
3 Structures and Processes of the Memory System 55
4 Knowledge 83
5 Skills and Expertise 111
6 Effects of Age, Intelligence, and Styles on Learning and Memory 135
7 Machine Learning: Symbolic and Connectionist 163
8 Applications 183
References 213
Index 243
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