Connectionism and the Mind: Parallel Processing, Dynamics, and Evolution in Networks / Edition 2

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Overview

Connectionism and the Mind, Second Edition introduces connectionist networks and explores theoretical and philosophical implications. Much of the discussion has been updated, and 2 new chapters have been added on the relation of connectionism to recent work on artificial life and dynamical models of cognition.

Connectionist models (also known as artificial neural network or parallel distributed processing models) implement the idea that complex cognitive operations can be carried out by very simple, neuron-like elements when they are assembled into networks by means of weighted connections. Intelligent performance is derived from the propagation of activation across units, and the fundamental cognitive activity is pattern recognition and completion.

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Editorial Reviews

From the Publisher
"Much more than just an update, this is a thorough and exciting re-build of the classic text. Excellent new treatments of modularity, dynamics, artificial life, and cognitive neuroscience locate connectionism at the very heart of contemporary debates. A superb combination of detail, clarity, scope, and enthusiasm." Andy Clark, University of Sussex

"Connectionism and the Mind is an extraordinarily comprehensive and thoughtful review of connectionism, with particular emphasis on recent developments. This new edition will be a valuable primer to those new to the field. But there is more: Bechtel and Abrahamsen's trenchant and even-handed analysis of the conceptual issues that are addressed by connectionist models constitute an important original theoretical contribution to cognitive science." Jeff Elman, University of California at San Diego

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Product Details

  • ISBN-13: 9780631207139
  • Publisher: Wiley
  • Publication date: 1/28/2002
  • Edition description: REV
  • Edition number: 2
  • Pages: 424
  • Product dimensions: 6.85 (w) x 9.75 (h) x 1.25 (d)

Meet the Author

William Bechtel is Professor of Philosophy at the University of California, San Diego and Editor of the journal Philosophical Psychology. His publications include Philosophy of Mind (1988), Philosophy of Science (1988), and Discovering Complexity (1993, with Robert Richardson), A Companion to Cognitive Science (with George Graham, Blackwell 1999), Philosophy and the Neurosciences (with Pete Mandik, Jennefer Mundale and Robert S. Stufflebeam, Blackwell 2001).

Adele Abrahamsen is Associate Professor of Psychology and Undergraduate Director of the Philosophy-Neuroscience-Psychology and Linguistics Programs at Washington University in St. Louis. She is the author of Child Language (1977).

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Table of Contents

Preface
1 Networks versus Symbol Systems: Two Approaches to Modeling Cognition 1
1.1 A Revolution in the Making? 1
1.2 Forerunners of Connectionism: Pandemonium and Perceptrons 2
1.3 The Allure of Symbol Manipulation 7
1.4 The Decline and Re-emergence of Network Models 12
1.5 New Alliances and Unfinished Business 15
2 Connectionist Architectures 19
2.1 The Flavor of Connectionist Processing: A Simulation of Memory Retrieval 19
2.2 The Design Features of a Connectionist Architecture 29
2.3 The Allure of the Connectionist Approach 45
2.4 Challenges Facing Connectionist Networks 51
3 Learning 54
3.1 Traditional and Contemporary Approaches to Learning 54
3.2 Connectionist Models of Learning 57
3.3 Some Issues Regarding Learning 82
4 Pattern Recognition and Cognition 89
4.1 Networks as Pattern Recognition Devices 90
4.2 Extending Pattern Recognition to Higher Cognition 102
4.3 Logical Inference as Pattern Recognition 106
4.4 Beyond Pattern Recognition 117
5 Are Rules Required to Process Representations? 120
5.1 Is Language Use Governed by Rules? 120
5.2 Rumelhart and McClelland's Model of Past-tense Acquisition 122
5.3 Pinker and Prince's Arguments for Rules 135
5.4 Accounting for the U-shaped Learning Function 141
5.5 Conclusion 152
6 Are Syntactically Structured Representations Needed? 156
6.1 Fodor and Pylyshyn's Critique: The Need for Symbolic Representations with Constituent Structure 156
6.2 First Connectionist Response: Explicitly Implementing Rules and Representations 163
6.3 Second Connectionist Response: Implementing Functionally Compositional Representations 170
6.4 Third Connectionist Response: Employing Procedural Knowledge with External Symbols 178
6.5 Using External Symbols to Provide Exact Symbol Processing 190
6.6 Clarifying the Standard: Systematicity and Degree of Generalizability 194
6.7 Conclusion 197
7 Simulating Higher Cognition: A Modular Architecture for Processing Scripts 200
7.1 Overview of Scripts 200
7.2 Overview of Miikkulainen's DISCERN System 201
7.3 Modular Connectionist Architectures 203
7.4 FGREP: An Architecture that Allows the System to Devise Its Own Representations 206
7.5 A Self-organizing Lexicon Using Kohonen Feature Maps 212
7.6 Encoding and Decoding Stories as Scripts 217
7.7 A Connectionist Episodic Memory 223
7.8 Performance: Paraphrasing Stories and Answering Questions 228
7.9 Evaluating DISCERN 231
7.10 Paths Beyond the First Decade of Connectionism 233
8 Connectionism and the Dynamical Approach to Cognition 235
8.1 Are We on the Road to a Dynamical Revolution? 235
8.2 Basic Concepts of DST: The Geometry of Change 237
8.3 Using Dynamical Systems Tools to Analyze Networks 243
8.4 Putting Chaos to Work in Networks 257
8.5 Is Dynamicism a Competitor to Connectionism? 264
8.6 Is Dynamicism Complementary to Connectionism? 276
8.7 Conclusion 280
9 Networks, Robots, and Artificial Life 282
9.1 Robots and the Genetic Algorithm 282
9.2 Cellular Automata and the Synthetic Strategy 284
9.3 Evolution and Learning in Food-seekers 291
9.4 Evolution and Development in Khepera 295
9.5 The Computational Neuroethology of Robots 300
9.6 When Philosophers Encounter Robots 301
9.7 Conclusion 305
10 Connectionism and the Brain 306
10.1 Connectionism Meets Cognitive Neuroscience 306
10.2 Four Connectionist Models of Brain Processes 309
10.3 The Neural Implausibility of Many Connectionist Models 341
10.4 Whither Connectionism? 346
App. A: Notation 349
App. B: Glossary 350
Bibliography 363
Name Index 384
Subject Index 395
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