Computation and cognition : Toward a foundation for cognitive science.

308 Pages·1985·22.606 MB·English

by  Zenon W. Pylyshyn

Computation and Cognition
db
Bradford Books
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Computation and Cognition
Toward a Foundation for Cognitive Science
Zenon W. Pylyshyn
A Bradford Book
The MIT Press
Cambridge, Massachusetts
London, England
Second edition , 1985
Copyright @ 1984 by
The 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 writing from the publisher.
This book was set in Palatino
by The MIT Press Computergraphics Department
and printed and bound by Halliday Lithograph
in the United States of America .
Library of Congress Cataloging in Publication Data
Pylyshyn, Zenon W., 1937-
Computation and cognition.
" A Bradford book ."
Bibliography: p.
Includes index .
1. Cognition. 2. Artificial intelligence.
I. Title .
BF311 .P93 1984 153' 84-2913
ISBN 0-262- 16098 -6
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Contents
Preface xi
What Is Cognitive Science? xi
Why Bother with Foundations? xvm
Some Personal Background and Intellectual Deb~s xxi
Chapter 1
The Explanatory Vocabulary of Cognition 1
Cognitive Phenomena and Folk Psychology 1
Capturing Generalizations 6
The Stimulus-Independence of Cognitive Behavior 12
Phenomena as "Events under Descriptions• 16
Chapter 2
The Explanatory Role of Representations 23
Introduction 23
The Appeal to Representations 24
Representational and Functional Levels 28
Representational Content as Defining a Level of Description 32
•Levels and Constraints on Realizability 35
Where Does the Semantic Interpretation Come From? 38
End Note 1: When Are Functional States Representations? 45
End Note 2: On the Notion of Representational Content 48
Chapter 3
The Relevance of Computation 49
Some Background: Fonnalism, Symbols, and Mechanisms 49
Computation as a Symbolic Process 54
Syntax and Semantics in Computation 59
·A Numerical Example 59
•Cognitive Rules and Syntax 62
·A Note on the Notion of "Computing" 69
The Role of Computer Implementation 74
•The Control Issue 78
viii Contents
Chapter 4
The Psychological Reality of Programs: Strong Equivalence 87
The Role of Functio11al Architecture 87
Functional Architecture and Computer Programs 93
·Algorithms' Dependerice 011 Fu11ctional Architecwre 95
Fu11ctio11al Architecture a11d Mental Processes 101
Chapter 5
Constraining Functional Architecture 107
The Level-of-Aggregation Problem 107
Some Methodological Proposals 111
Complexity Equivalence 114
• Strong-Equivale11ce and Reactio11-Time Measures 120
Cognitive Pwetrability 130
·Is Everythi11g Cognitively Pe11etrable? 140
Chapter 6
The Bridge from Physical to Symbolic: Transduction 147
Introduction 147
• Co11tact between Mecha11ism a11d E11vironment 149
•The Transducer Function 151
Criteria for a Psychological Transducer 153
• Tlte Frmction of a Transducer ls Nonsymbolic 154
·A Tra11sd11cer Is Primarily Stimulus-Bound 155
•A Transducer Output Is an Atomic Symbol (or tr-tuple) 158
·Transducer Inputs Must Be Stated in the La11g11age of Physics 165
Additio11al Constraints 011 Transducers 171
•Can Tra11sducers Be Identified by Neurophysiological Methods? 171
·Can Transducers Be f dentified by P~ychophysical Methods? 173
•Can Transducers Be l dentified by Fu11ctional Analysis? 176
•Summary 178
Some Co11sequences of this Approach: Is Perception "Direct"? 179
•"Ecological Optics" and the Perceptio11 of Spatial Layout 180
•Detecting In varia11ce 187
•Temporal Order and Memory 188
Chapter 7
Functional Architecture and Analogue Processes 193
Reaso11ing and the Language of Thought 193
The Concept of an A11alog11e Process 197
·The Attractio11 of A11alog11es 197
•What Makes Something an A11alogue Process? 199
Contents ix
Forms of Constraint on Processes: The Notion of Capacity 203
• fotrinsic versus Semantic Constraints 205
•Explanation and Functional Architecture 210
The Search for Fixed Architectural Functio!1s 216
Chapter 8
Mental Imagery and Functional Architecture 225
Introduction: The Autonomy of the Imagery Process 225
Tacit Knowledge and "Mental Scanning" 231
•The Empirical Phenomena: Mental Scanning 231
·Some Preliminary Considerations 233
•Task Demands of Imagery Experiments 236
•The Generality of the "Tacit Knowledge• View 238
•Some Empirical Evidence 242
Other Arguments against the Tacit-Knowledge View 245
•Access to Tacit Knowledge 245
•Combining Imagery and Vision 247
What Theoretical Claim About Imagery Is Being Made? 251
Chapter 9
Epilogue: What Is Cognitive Science the Science of? 257
Summary of Assumptions 257
Carving Nature at the Joints 263
Some Possible Noncognitive Effects: Leaming, Development, and
Moods 266
References 273
Index 285
Preface
(cid:0)
What Is Cognitive Science?
This book concerns the foundational assumptions of a certain approach
to the study of the mind , which has lately become known as cognitive
science. A more realistic way to put it might be to say that the material
contained here is to the foundations of cognitive science what a hole
in the ground is to the foundation of a house. It may not seem like
what you eventually hope to have, but you do have to start some place.
It is possible that despite considerable recent interest in the field,
and despite the appearance of much commonality , cognitive science
may have no single foundation ; it may be just an umbrella title for a
number of different sciences, all of which are, like the proverbial blind
men trying to understand the elephant , attempting to understand the
workings of the mind . If that is the case, cognitive science might be
simply a political union based on an interest in a broad set of questions ,
and perhaps on a shared need for certain techniques , say, experimental
methods or the techniques of computer simulation . Academic departments
, st;ich as schools of engineering or departments of psychology ,
are probably based on just such ties. '
But there is another , much more exciting possibility : the prospect
that cognitive science is a genuine scientific domain like the domains
of chemistry , biology , economics , or geology . In scientific domains it
is possible to develop theories based on a special vocabulary or rea-
sonably uniform set of principles independent of the principles of other
sciences- that is, principles with considerable autonomy . Many feel,
as I do, that there may well exist a natural domain corresponding
roughly to what has been called "cognition ," which may admit of such
a uniform set of principles . Just as the domain of biology includes
something like all living thil:lgs (for which a strict definition is probably
impossible outside of biological theory ), so the domain of cognitive
science may be something like "knowing things ," or, as George Miller
(1984) colorfully dubbed it, the "informavores ."
Humans are living things , and consequently advances in biological
XII Preface
science will contribute to a fuller understanding of human nature . Similarly
, because we are informavores , or cognizers, understanding human
nature can also gain from the study of principles governing members
of that domain . At the moment it appears that included in this category
are the higher vertebrates and certain computer systems. In any case,
in view of the kinds of considerations we will explore in this book,
and the impressive succes ses in recent work on artificial intelligence ,
one ought to take such a possibility seriously .
Lest the prospect of being a sibling of the computer appear as disturbing
as the prospect of being the nephew or niece of the great ape
once was, we should keep in mind that these are merely ways of
classifying individuals for the purpose of discovering some of their
operating principles . After all, we are classified along with rocks, atoms,
and galaxies for the purpose of revealing how we move in response
to physical forces. No classification - including "parent," "sentient
being," or "fallen angel"- can capture all that is uniquely human .
Indeed , even considering all the natural kinds to which we belong will
not render a vision of humans as "merely " something or other; but
each gives us special insight into some aspect of our nature .
What , then, is the common nature of members of the class of cog-
nizers? I will suggest that one of the main things cognizers have in
common is, they act on the basis of representations. Put another way,
to explain important features of their behavior , we must take into account
their (typically tacit) knowledge and goals. Knowing the representations
they possess, together with the assumption that much of their behavior
is connected with their representations by certain general principles ,
we can explain an important segment of the regularities in behavior
exhibited by these cognizers . This view (sometimes called the "representational
theory of mind ") is what brings the study of cognition
into contact with both classic philosophical problems (the sort of problem
that concerned Franz Brentano when he talked about the "intentionality
of the mental ") and ideas from computer science. In chapters 1 and 2
I introduce this set of issues in the context of the demands placed on
the task of providing psychological explanations .
Even assuming that this general picture is correct, it raises important
and deep puzzles . How is it possible for a physical system (and I assume
that cognizers are physical systems) to act on the basis of "knowledge
of" objects and relations to which the system is not causally connected
in the correct way? Clearly , the objects of our fears and desires do not
cause behavior in the same way that forces and energy cause behavior
in the physical realm . When my desire for the pot of gold at the end
of the rainbow causes me to go on a search, the (nonexistent ) pot of
gold is not a causal property of the sort that is involved in natural