Cognitive Science: An Introduction to the Study of Mind / Edition 2

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Substantially revised, this Second Edition includes the latest breakthroughs in this fast-moving field. The authors present emerging areas of network science, dynamical systems theory, behavioral economics, and animal intelligence and tie each area to discoveries in psychology, neuroscience, and cognition. Major findings are placed in the context of the theories and models of cognition and critically evaluated. Providing a unifying framework, pedagogical features help students understand the different methodologies and perspectives in cognitive science.
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Editorial Reviews

Kathleen M. Galotti
“I like the Friedenberg and Silverman Cognitive Science because I've found it to be a more inviting entree to this complex interdisciplinary field than other texts I've previously used. The authors really do a fine job distilling the essential questions from each discipline that contributes to cognitive science for novice students. End-of-chapter reviews are thought-provoking. I'm eagerly awaiting the second addition, with its excellent additional chapters on social and emotional cognition. I think it will improve an already great teaching resource!”
Marc Pomplun
"The strength of this book is the systematic introduction of the disciplines, methods, and viewpoints that constitute cognitive science. Other books are not as systematic and comprehensive on the overall endeavor of cognitive science. They do not as systematically evaluate different viewpoints as this book does."
Emanual Mason
"I like the inclusion of the new chapters on emotional cognition and social cognition. The most impressive aspect of this book to students is its ability to make a large amount of complex material accessible to students."
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Product Details

  • ISBN-13: 9781412977616
  • Publisher: SAGE Publications
  • Publication date: 7/14/2011
  • Edition description: Second Edition
  • Edition number: 2
  • Pages: 544
  • Sales rank: 1,242,573
  • Product dimensions: 7.40 (w) x 9.00 (h) x 1.20 (d)

Meet the Author

Jay Friedenberg is Chair and Professor of the Psychology Department at Manhattan College, where he directs the Cognitive Science program. He obtained his Ph.D. in cognitive psychology in 1995 at the University of Virginia. He is interested in both vision and the philosophy of mind. He teaches courses in physiological psychology, learning and cognition, sensation and perception, and cognitive science. Dr. Friedenberg has published several articles on visual estimation of center of mass. His current research projects are investigating image statistics, picture perception, and the aesthetics of geometrical shapes. He has published books on artificial intelligence, chaos theory and psychology. He is a member of the Eastern Psychological Association, the Vision Science Society, The Psychonomic Society and Phi Beta Kappa.

Gordon Silverman is Chair of Electrical and Computer Engineering at Manhattan College. His professional career spans more than 50 years of corporate, teaching, consulting, and research experience, during which he has developed a range of scientific instruments, particularly for use in physiological psychology research environments. He is the holder of eight patents, some related to behavior modification. The author of more than 20 journal articles and books, he has also served on the faculties of The Rockefeller University and Fairleigh Dickinson University. Dr. Silverman’s current research interests include telemedicine, rehabilitation medicine, artificial intelligence, and biomedical instrumentation and modeling.

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Table of Contents

1. Introduction: Exploring Inner Space
A Brave New World
What Is Cognitive Science?
The Interdisciplinary Perspective
Interdisciplinary Crossroads: The Philosophy and Psychology of Mental Representation
Summing Up: Review of Chapter 1
2. The Philosophical Approach: Enduring Questions
What Is Philosophy?
The Mind-Body Problem
The Knowledge Acquisition Problem
The Mystery of Consciousness
Overall Evaluation of the Philosophical Approach
Interdisciplinary Crossroads: Philosophy, Neuroscience and Binocular Rivalry
Summing Up: Review of Chapter 2
3. The Psychological Approach: A Profusion of Theories
What Is Psychology?
Psychology and the Scientific Method
Mental Atoms, Mental Molecules, and a Periodic Table of the Mind: The Voluntarist Movement
Structuralism: What the Mind Is
Functionalism: What the Mind Does
The Whole Is Greater Than the Sum of Its Parts: Mental Physics and the Gestalt Movement
Mini-Minds: Mechanism and Psychoanalytic Psychology
Mind as a Black Box: The Behaviorist Approach
Overall Evaluation of the Psychological Approach
Interdisciplinary Crossroads: Gestalt Phenomenology, Experimental Psychology and Perceptual Grouping
Summing Up: A Review of Chapter 3
4. The Cognitive Approach I: Vision, Pattern Recognition and Attention
Some History First: The Rise of Cognitive Psychology
The Cognitive Approach: Mind as an Information Processor
Modularity of Mind
Theories of Vision and Pattern Recognition
Theories of Attention
Evaluating the Model-Building Approach
Interdisciplinary Crossroads: Computational Vision and Pattern Recognition
Summing Up: A Review of Chapter 4
5. The Cognitive Approach II: Memory, Imagery, and Problem Solving
Types of Memory
Memory Models
Visual Imagery
Problem Solving
Overall Evaluation of the Cognitive Approach
Interdisciplinary Crossroads: Artificial Intelligence, Problem Solving and the SOAR Model
Summing Up: A Review of Chapter 5
6. The Neuroscience Approach: Mind As Brain
The Neuroscience Perspective
Methodology in Neuroscience
Modern Brain Imaging Methods
Brain Stimulation Techniques
The Small Picture: Neuron Anatomy and Physiology
The Big Picture: Brain Anatomy
The Neuroscience of Visual Object Recognition
The Neuroscience of Attention
Disorders of Attention
The Neuroscience of Memory
Neural Substrates of Working Memory
Neural Substrates of Long-Term Memories
The Neuroscience of Executive Function and Problem Solving
Overall Evaluation of the Neuroscience Approach
Interdisciplinary Crossroads: Perceptual Binding and Neural Synchrony
Summing Up: A Review of Chapter 6
7. The Network Approach: Mind as a Web
The Network Perspective
Artificial Neural Networks
Semantic Networks: Meaning in the Web
Network Science
Overall Evaluation of the Network Approach
Interdisciplinary Crossroads: Emotions and Networks
Summing Up: A Review of Chapter 7
8. The Evolutionary Approach: Change Over Time
The Evolutionary View
A Little Background: Natural Selection and Genetics
Comparative Cognition
Evolutionary Psychology
Overall Evaluation of the Evolutionary Approach
Interdisciplinary Crossroads: Evolutionary Processes and Artificial Life
Summing Up: A Review of Chapter 8
9. The Linguistic Approach: Language and Cognitive Science
The Linguistic Approach: The Importance of Language
The Nature of Language
Language Use in Primates
Language Acquisition
Language Deprivation
Cognition and Linguistics: The Role of Grammar
Neuroscience and Linguistics: The Wernicke-Geschwind Model
Artificial Intelligence and Linguistics: Natural Language Processing
Overall Evaluation of the Linguistic Approach
Interdisciplinary Crossroads: Language, Philosophy and the Linguistic Relativity Hypothesis
Summing Up: A Review of Chapter 9
10. The Emotional Approach: Mind as Emotion
What is Emotion?
Basic Emotions
Theories of Emotion
Hot and Cold: Emotion-Cognition Interactions
Emotions and Neuroscience
Emotions, Evolution and Psychological Disorders
Emotions and Artificial Intelligence: Affective Computing
Overall Evaluation of the Emotional Approach
Interdisciplinary Crossroads: Emotion, Robotics and the Kisment Project
Summing Up: A Review of Chapter 10
11. The Social Approach: Mind as Society
Social Cognition
Evolution and Social Cognition
Attention and Social Cognition
Social Cognitive Neuroscience
Theory of Mind
Other Social Cognitive Disorders
Overall Evaluation of the Social Approach
Interdisciplinary Crossroads: Game Theory and Prisoner’s Dilemma
Summing Up: A Review of Chapter 11
12. The Artificial Intelligence (AI) Approach I: The Mind As Machine
Cognitive Science from the AI Perspective
Historical Precursors
Universal Computation and Turing’s Contribution
The Turing Test
Evaluating the Work of Turing’s Universal Computing Machine
Predictive Architectures and Their Physical Challenges
Evaluating Machine Computational Limitations
Artificial General Intelligence (AGI)
Evolutionary Computing
Evaluation of Evolutionary Computing and Artificial General Intelligence
Agent-Based Architectures
Multiagent Systems
Overall Evaluation of the Computer as a Model of Brain Organization
Interdisciplinary Cross-Roads*fill in later
13. Artificial Intelligence II: Embodiments and Robotics
The IA Paradigm
Why Biology is Important
Modeling Aspects of Biological Systems
Abstracting General Principles of IAs
Embodiment and situational aspects of intelligent behavior
Relationships between elements of the IA system (structure) and the environment
Applying the principles to the design of IAs
Cognitive Models of IAs
Deep Blue and the Chess Master
Can an IA “learn” to play a winning game without knowing anything about the game?
Expert Systems – a culminating “top-down” example
Why Not Build a Brain – the Blue Brain Project
Robotic Embodiments – Ultimate IAs
Defining a robotic embodiment
The IA Embodiment Paradigm Explored
Robotic Architectures
Hierarchical Architectures
Reactive Architectures
The Hybrid Deliberative/Reactive Paradigm
Biological and Social Influences on Robots
Swarming – what animals can teach us.
Robotic Simulation
Overall Evaluation of an IA Embodiment
Interdisciplinary Cross-Roads: Where Biology Meets Technology
Summing Up: A Review of Chapter 13
14. Conclusion: Where We Go From Here
The Benefits of Cognitive Science
Issues in Cognitive Science
The Dynamical Systems Approach
Dynamical Representation
Dynamical vs. Classical Cognitive Science
Evaluating the Dynamical Perspective
Integrating Cognitive Science
The Future
Interdisciplinary Crossroads: Multiple Approaches to Levels of Explanation in Cognitive Science
Summing Up: A Review of Chapter 14
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