Minds and Machines
Connectionism and Psychological Modeling
Erschienen am 8. Mai 2008
296 Seiten
978-0-470-75298-2 (ISBN)
Beschreibung
Minds and Machines: Connectionism and Psychological Modelingexamines different kinds of models and investigates some of thebasic properties of connectionism in the context of syntheticpsychology, including detailed accounts of how the internalstructure of connectionist networks can be interpreted.
* * Introduces connectionist models as tools that are bothsynthetic and representational and which can be used as the basisfor conducting synthetic psychology.
* Includes distinctively varied account of modeling, historicaloverview of the synthetic approach, and unique perspectives onconnectionism.
* Investigates basic properties of connectionism in the contextof synthetic psychology, including detailed accounts of how theinternal structure can be interpreted.
* Provides supplementary material online atwww.bcp.psych.ualberta.ca/~mike/Book2/ which includes free softwarefor conducting connectionist simulations and instructions forbuilding simple robots.
Rezensionen / Stimmen
"In this remarkable book, Dawson refines and developssynthetic psychology - an approach to explainingmental capacities that takes as its inspiration the investigationof simple systems exhibiting emergent behavior. Rich with examples,the book shows with extraordinary clarity how ideas from embodiedcognitive science, robotics, artificial life, and connectionism canbe combined to shed new light on the workings of the mind. It'shard to imagine a better book for anyone wishing to understand thelatest advances in cognitive science." Larry Shapiro, Universityof Wisconsin "Minds and Machines provides an easily understoodintroduction to synthetic psychology - start with simpleprocesses, see what emerges, and analyze the resulting system.Dawson lays a solid foundation describing the strengths andweaknesses of various modeling approaches in psychology, and thenbuilds on this by giving concrete examples of how connectionism- using the synthetic approach - can be used to providesimple explanations of seemingly complex cognitive phenomena."David A. Medler, The Medical College of Wisconsin "Thisis a wonderful book, both in terms of the thought-provokingtechnical content and the delightfully conversational style thatreaders have come to expect from the author of UnderstandingCognitive Science. Dawson has a real gift for presentingcomplex ideas in an accessible and engaging way that does notdilute the scientific or philosophical intricacies involved."Stefan C. Kremer, University of Guelph, Canada "An important virtue of this book is that the content and orderof presentation has clearly been tested at length in the classroomof a dedicated and creative teacher. The book has manyillustrations from teaching practice, and would be an excellentbasis for a senior undergraduate or introductory graducate courseon cognitive modelling, and I'd be delighted to use it for thatpurpose myself ... This is a fine book, and I suspect it would be avaluable resource for those who don't know much about syntheticpsychology but would like to get a clear sense of the lie of theland." David Spurrett, University of KwaZulu-Natal, Psychologyin Society, 30, 2004, 77-79Weitere Details
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Person
Michael R. W. Dawson is a member of the Department of Psychology and the Biological Computation Project at the University of Alberta, Canada. His primary research interests concern the foundations of cognitive science, learning and representation in connectionist networks, and computational models of motion perception. He is the author of Understanding Cognitive Science (Blackwell Publishers, 1998).
Inhalt
List of Figures.
List of Tables.
1. The Kids in the Hall.
Synthetic Versus Analytic Traditions. .
2. Advantages and Disadvantages of Modeling.
What Is A Model?.
Advantages and Disadvantages of Models. .
3. Models of Data.
An Example of a Model of Data.
Properties of Models of Data. .
4. Mathematical Models.
An Example Mathematical Model.
Mathematical Models vs. Models of Data. .
5. Computer Simulations.
A Sample Computer Simulation.
Connectionist Models.
Properties of Computer Simulations. .
6. First Steps Toward Synthetic Psychology.
Introduction.
Building a Thoughtless Walker.
Step 1: Synthesis.
Step 2: Emergence.
Step 3: Analysis.
Issues Concerning Synthetic Psychology. .
7. Uphill Analysis, Downhill Synthesis.
Introduction.
From Homeostats to Tortoises.
Ashby's Homeostat.
Vehicles.
Synthesis and Emergence: Some Modern Examples.
The Law of Uphill Analysis and Downhill Synthesis. .
8. Connectionism As Synthetic Psychology.
Introduction.
Beyond Sensory Reflexes.
Connectionism, Synthesis, and Representation.
Summary and Conclusions. .
9. Building Associations.
From Associationism To Connectionism.
Building An Associative Memory.
Beyond the Limitations of Hebb Learning.
Associative Memory and Synthetic Psychology. .
10. Making Decisions.
The Limits of Linearity.
A Fundamental Nonlinearity.
Building a Perceptron: A Nonlinear Associative Memory.
The Psychology of Perceptrons.
The Need for Layers. .
11. Sequences of Decisions.
The Logic of Layers.
Training Multilayered Networks.
A Simple Case Study: Exclusive Or.
A Second Case Study: Classifying Musical Chords.
A Third Case Study: From Connectionism to Selectionism..
12. From Synthesis To Analysis.
Representing Musical Chords in a Pdp Network.
Interpreting the Internal Structure of Value Unit Networks.
Network Interpretation and Synthetic Psychology. .
13. From Here To Synthetic Psychology.
References.
Index
