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1、Mechanisms of Implicit Learning title:Mechanisms of Implicit Learning : Connectionist Models of Sequence Processing Neural Network Modeling and Connectionism author:Cleeremans, Axel. publisher:MIT Press isbn10 | asin:0262032058 print isbn13:9780262032056 ebook isbn13:9780585020389 language:English s
2、ubject Neural networks (Computer science) , Implicit learning, Connection machines. publication date:1993 lcc:QA76.87.C54 1993eb ddc:006.3/3 subject:Neural networks (Computer science) , Implicit learning, Connection machines. cover Page ii Neural Network Modeling and Connectionism Jeffrey L. Elman,
3、Editor Connectionist Modeling and Brain Function: The Developing Interface Stephen Jos Hanson and Carl R. Olson, editors Neural Network Design and the Complexity of Learning J. Stephen Judd Neural Networks for Control W. Thomas Miller, Richard Sutton, and Paul J. Werbos, editors The Perception of Mu
4、ltiple Objects: A Connectionist Approach Michael Mozer Neural Computation of Pattern Motion: Modeling Stages of Motion Analysis in the Primate Visual Cortex Margaret Euphrasia Sereno Subsymbolic Natual Language Processing: An Integrated Model of Scripts, Lexicon, and Memory Risto Miikkulainen Analog
5、y-Making as Perception: A Computer Model Melanie Mitchell Mechanisms of Implicit Learning: Connectionist Models of Sequence Processing Axel Cleeremans page_ii Page iii Mechanisms of Implicit Learning Connectionist Models of Sequence Processing Axel Cleeremans A Bradford Book The MIT Press Cambridge,
6、 Massachusetts London, England page_iii Page iv 1993 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in wri
7、ting from the publisher. This book was set in Palatino by The MIT Press and was printed and bound in the United States of America. Library of Congress Cataloging-in-Publication Data Cleeremans, Axel. Mechanisms of implicit learning: connectionist models of sequence processing / Axel Cleeremans. p. c
8、m. (Neural Network modeling and connectionism) “A Bradford book.“ Includes bibliographical references and index. ISBN 0-262-03205-8 1. Neural networks (Computer science) 2. Implicit learning. 3. Connection machines. I. Title. II. Series. QA76.87.C54 1993 006.33dc20 92-35739 CIP page_iv Page v A lenf
9、ant invisible page_v Page vii Contents Series Forewordix Prefacexi Acknowledgmentsxiii Chapter 1 Implicit Learning: Explorations in Basic Cognition1 Introduction1 Empirical Studies of Implicit Learning5 Models and Mechanisms19 Chapter 2 The SRN Model: Computational Aspects of Sequence Processing35 L
10、earning a Finite-State Grammar39 Discovering and Using Path Information49 Learning58 Encoding Nonlocal Context63 Discussion70 Chapter 3 Sequence Learning as a Paradigm for Studying Implicit Learning75 Learning the Structure of Event Sequences76 Experiment 181 Experiment 291 Simulation of the Experim
11、ental Data95 General Discussion103 Conclusion112 Chapter 4 Sequence Learning: Further Explorations113 Sequence Learning and Memory Disorders114 Attention and Sequence Structure116 Elementary Sequence Learning and the Effects of Explicit Knowledge123 General Discussion134 page_vii Page viii Chapter 5
12、Encoding Remote Context137 Long-Distance Contingencies and Prediction-Based Learning137 Comparison with Other Architectures for Sequence Processing139 An Empirical Test144 Experiment 3157 Discussion164 Chapter 6Explicit Sequence Learning169 An Explicit Prediction Task169 Transfer to New Material183
13、Chapter 7General Discussion189 Prediction-Relevance and Context Representation191 Attention, Awareness, and the Role of Explicit Knowledge194 Conscious and Unconscious Knowledge197 Transfer and Abstraction200 On Modeling205 Conclusion206 Notes209 References213 Index221 page_viii Page ix Series Forew
14、ord The goal of this series, Neural Network Modeling and Connectionism, is to identify and bring to the public the best work in the exciting field of neural network and connectionist modeling. The series includes monographs based on dissertations, extended reports of work by leaders in the field, ed
15、ited volumes and collections on topics of special interest, major reference works, and undergraduate and graduate-level texts. The field is highly interdisciplinary, and works published in the series will touch on a wide variety of topics ranging from low-level vision to the philosophical foundation
16、s of theories of representation. Jeffrey L. Elman, Editor Associate Editors: James Anderson, Brown University Andrew Barto, University of Massachusetts, Amherst Gary Dell, University of Illinois Jerome Feldman, University of California, Berkeley Stephen Grossberg, Boston University Stephen Hanson, Princeton University Geoffrey Hinton, University of Toronto Michael Jordan, MIT James McClelland, Carnegie Mellon University Domenico Parisi, Instituto di Psicologia del CNR David Rumelhart, Stanf
