Synopses & Reviews
This book presents a vital resource -- a comprehensive interdisciplinary selection of seminal papers in the foundations of cognitive science, from leading figures in artificial intelligence, linguistics, philosophy, psychology, and neuroscience.
The collection is organized around three broad conceptions of the mind: the mind as computer program, the mind as a neural network, and the mind as brain. Each category includes papers that articulate the conception in question, papers that illustrate it, papers that interpret or criticize it, and papers that provide necessary technical background.
Finally, there is a section of classic papers on four broad questions which have shaped contemporary thinking in cognitive science:
What is innate in the mind?
Is the mind a seamless whole, or is it made up of independent modules that differ significantly from each other?
Are our ordinary mental concepts, such as belief, desire, and intention, a good starting place for a scientific understanding of the mind, or are they artifacts of a pre-scientific conception that should be discarded?
How should biology generally, and the evolution of animals in particular, constrain our theories about mental phenomena?
Taken together, these papers give a sense of the history of the field as well as its contents by presenting the argumnets, models, data, and experiments that most crucially influence theory and practice in cognitive science.
Review
"This anthology features papers that are historically important to cognitive science, giving about equal billing to symbolic, connectionist, and neuroscience viewpoints. Although the papers convey some key findings, their strong point is clarifying assumptions that underlie these three perspectives. Students will find this a valuable sourcebook for the major research traditions." Lance Rips, Northwestern University
Synopsis
This book presents a vital resource -- a comprehensive interdisciplinary selection of seminal papers in the foundations of cognitive science, from leading figures in artificial intelligence, linguistics, philosophy, psychology, and neuroscience. The collection is organized around three broad conceptions of the mind: the mind as computer program, the mind as a neural network, and the mind as brain. Each category includes papers that articulate the conception in question, papers that illustrate it, papers that interpret or criticize it, and papers that provide necessary technical background. Finally, there is a section of classic papers on four broad questions which have shaped contemporary thinking in cognitive science: What is innate in the mind? Is the mind a seamless whole, or is it made up of independent modules that differ significantly from each other? Are our ordinary mental concepts, such as belief, desire, and intention, a good starting place for a scientific understanding of the mind, or are they artifacts of a pre-scientific conception that should be discarded? How should biology generally, and the evolution of animals in particular, constrain our theories about mental phenomena? Taken together, these papers give a sense of the history of the field as well as its contents by presenting the argumnets, models, data, and experiments that most crucially influence theory and practice in cognitive science.
Synopsis
Minds, Brains, and Computers presents a vital resource -- the most comprehensive interdisciplinary selection of seminal papers in the foundations of cognitive science, from leading figures in artificial intelligence, linguistics, philosophy, psychology, and neuroscience.
About the Author
Robert Cummins is Professor of Philosophy at the University of California, Davis. He is the author of
The Nature of Psychological Explanation (1983),
Meaning and Mental Representation (1987), and
Representations, Targets and Attitudes (1996), as well as many articles and several edited volumes. He specializes in the foundations of cognitive science and the nature of mental representation.
Denise D. Cummins is Associate Research Professor of Social Sciences at the University of California, Davis. She is the author of The Other Side of Psychology (1995), The Evolution of Mind (ed. with Colin Allen), and Human Reasoning: an Evolutionary Perspective as well as numerous articles and reviews. She specializes in higher cognition from an evolutionary perspective.
Table of Contents
Preface.
Part I: The Mind as Computer: Introduction:.
1. A History of Thinking: D. D. Cummins.
2. Minds and Machines: H. Putnam.
3. Semantic Engines: An Introduction to Mind Design: J. Haugeland.
4. The Language of Thought: J. A. Fodor.
5. Vision: D. Marr.
6. GPS, A Program that Simulates Human Thought: A. Newell and H. Simon.
7. A Procedural Model of Language Understanding: T. Winograd.
8. A General Learning Theory and its Application to Schema Abstraction: J. R. Anderson and P. J. Kline.
9. Minds, Brains, and Programs: J. R. Searle.
10. Computing, Machinery, and Intelligence: M. Turing.
Part II: The Mind as Neural Network: Introduction: .
11. The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brian: F. Rosenblatt.
12. Cognitive Activity in Artificial Neural Networks: P. M. Churchland.
13. Cooperative Computation of Stereo Disparity: D. Marr and T. Poggio.
14. On Learning the Past Tenses of English Verbs: D. E. Rumelhart and J. L. McClelland.
15. Parallel Networks that Learn to Pronounce English Text: T. J. Sejnowski and C. R. Rosenberg.
16. Connectionism and the Problem of Systematicity: Why Smolensky's Solution Won't Work: J. A. Fodor and B. P. McLaughlin.
17. Connectionism and the Language of Thought: P. Smolensky.
18. Rules and Connections in Human