Situated Cognition:

On Human Knowledge and Computer Representations

William J. Clancey


© Cambridge University Press 1997

 

CONTENTS

Introduction: What is situated cognition?

Descriptions and coordinations
On comparing human knowledge and computer representations
Reader's guide

 

PART I REPRESENTATIONS AND MEMORY

1. Aaron's Drawing

Plans, drawings, and interpretations
Mechanisms vs. descriptions of behavior
Aaron's program vs. what an artist knows
The experience of an artist participating in a community
The structural and functional aspects of "situatedness"

2. Mycin's Map

A simple introduction to knowledge representations
A knowledge base is a kind of map
General vs. situation-specific models
Searching a descriptive model
The map isn't the territory
Explaining rules
Syntactic and semantic interpretation

3. Remembering Controversies

Arguments for memory as dynamic process, against structure storage
How descriptive modelers talked about symbols and representations
The psychological view of a physical symbol system
The stored-schema view takes hold
"Actively doing something all the time"-From Associationism to Contextualism
Classical memory: Stored traces and isolated modules
What's wrong with simple connectionism?

4. Sensorimotor Maps vs. Encodings

von Foerster and Bateson: Descriptions of information
The owl monkey's map
Dynamic, systemic processes of representing
Maturana: In-formation vs. In-struction
Dewey: Coordination memory

 

PART II SITUATED ROBOTS

5. Navigating Without Reading Maps

Parallel, layered machines
Cooperating, self-organizing robots
Toto: Recognizing landmarks, learning paths
How Toto creates and uses maps
Appraisal of Toto
Pengi: Indexical representations
How Pengi uses labels
Talking about representations
Classical conditioning architecture
Computational neuroethology
Comparison and assessment of minimalist robots

6. Perceiving Without Describing

What mediates behavior?
A feature-learning robot
A chaotic model of perception
How a rabbit discriminates odors
Implications for a theory of perception

7. Remembering Without Matching

Neural Darwinism: An alternative to the encoding view of learning
Neuronal groups and classification
Coordinating categorizations by global maps: sequences and concepts
Design of Darwin III: Synthetic neural systems
A situated cognition interpretation of Neural Darwinism
Prometheus: Coupled recognition-action machines
Probabilistic topological maps
Coupling of perception and action
Summary of neuropsychological claims

8. Engineering Transactional Systems

Frames of reference for describing knowledge
The transactional perspective
Comparison of mechanisms of representing and coordinating motions
Behavior systems, development, and emergence
Methods for developing new behaviors
An evolutionary perspective on adaptation
Does AI need artificial life first?
The conceptualization problem

 

PART III ECOLOGICAL THEORIES

9. Transactional Experience

A message in Nice
Inventing a synthetic paintbrush
Contextualism revisited: No elementary properties
Conceptual composition over time: Consciousness, feedback, and error

10. Dialectic Mechanism

The philosophy of change
"Both-and" logic
Examples of dialectic relations
Conceptual dependency hierarchies
Scientific levels as dialectic

11. The Ecological Approach to Perception

Towards the reconcilation of the "situated" and the "symbolic" views
The reciprocal view of knowledge
Towards a theory of "knowing about"
Niches, affordances, and invariants
Energy and information
Gibson on information and perception
Different views of "construction" and "contained in"
Relating perception and conception

 

PART IV SYMBOLS RECONSIDERED

12. Coupling vs. Inference

Putting inference in its place
Examples of direct perception in people
The debate: What theorists misunderstood or poorly explained
Direct = without inference, not without processing at all
Information = invariant (stable) dynamic relation, not an isolated representation
Algorithmic theory = description, not a mechanism
Gibson: Perception = resonance mental = symbolic;
Ullman: Perception = symbolic mental = subjective
Perceptual = categorical, but not conceptual
Gibson's interpreters respond
Shaw and Todd: Abstract machine theory
Grossberg: Adaptive resonance
Reed: Perceiving is an act
Prazdny: The symbolic account is more eccentric
Bickhard: Functional indicators
Fodor and Pylyshyn: Perceiving is knowing what you know about
Correlation as a semantic relation
Relation of perception to beliefs, inference, and judgment

13. The Varieties of Symbol Systems

Reformulating the physical symbol system hypothesis
Symbolic meaning vs. "distal access"
How to develop a broader view of symbol systems
Diverse examples of "symbols"
Reconsidering human reasoning
The varieties of conceptual relations
Heuristic coordination

14. Reformulated Dilemmas

The procedural-declarative controversy
Elementary deliberation: Serial vs. parallel, Thinking vs. reflexes
The frame problem
Symbol grounding
Searle's Chinese room
What transfers?

Conclusions: Lessons for Cognitive Science

Clarifications about situated cognition
How to participate in a scientific controversy
Beware an either-or mentality
Try both narrow and broad interpretations of terms
Given a dichotomy, ask what both assume
Beware imposing spatial metaphors
Beware locating relations
Try viewing "independent" levels as co-determined
Don't equate a descriptive model with the causal process being described
Recognize that first approximations are often overstatements
Beware that words can sometimes mean their opposites
Enduring dilemmas are possibly important clues
Periodically revisit what you have chosen to ignore
Beware of building your theory into the data
Locate your work within historical debates and trends
"It's not new" does not refute a hypothesis
Beware errors of logical typing
Recognize conceptual barriers to change
To understand an incomprehensible position, start with what the person is against
Recognize that the "born again" mentality conceives sharp contrasts
Recognize how different disciplines study and use as tools different aspects of intelligence
Recognize the different mental styles of your colleagues
A proper treatment of descriptive modeling
Notes
References
Author Index
Subject Index

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