Cognitive Science provides a comprehensive introduction to the field from multiple perspectives to help readers better understand and answer questions about the mysteries of the mind. In each chapter, the authors focus on a particular area in cognitive science, exploring methodologies, theoretical perspectives, and findings, then offering the critical evaluations and conclusions drawn from them. Substantially updated with new and expanded content, the Third Edition reflects the latest research in this rapidly evolving field.
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A comprehensive undergraduate introduction to cognitive science, supported by password protected online lecturer resources.
Chapter 1: Exploring Inner Space A Brave New World What Is Cognitive Science? Representation Computation The Interdisciplinary Perspective Chapter 2: The Philosophical Approach: Enduring Questions What Is Philosophy? The Mind-Body Problem-What is Mind? Monism Dualism Functionalism- Are Minds Limited to Brains? The Knowledge Acquisition Problem- How Do We Acquire Knowledge? The Mystery of Consciousness- What is Consciousness and How Does it Operate? Chapter 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 Chapter 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- How do We Pay Attention? Evaluating the Model-Building Approach Chapter 5: The Cognitive Approach II: Memory, Imagery, and Problem Solving Types of Memory- How do we Remember? Memory Models Visual Imagery- How do we Imagine Problem Solving- How do we Solve Problems? Chapter 6: The Neuroscience Approach: Mind as Brain The Neuroscience Perspective Methodology in Neuroscience The Small Picture: Neuron Anatomy and Physiology The Big Picture: Brain Anatomy The Neuroscience of Visual Object Recognition The Neuroscience of Attention The Neuroscience of Memory Neural Substrates of Working Memory The Neuroscience of Executive Function and Problem Solving Chapter 7: The Network Approach: Mind as a Web The Network Perspective Artificial Neural Networks Characteristics of Artificial Neural Networks Early Conceptions of Neural Networks Back Propagation and Convergent Dynamics Evaluating the Connectionist Approach Semantic Networks: Meaning in the Web Network Science Chapter 8: The Evolutionary Approach: Change Over Time The Evolutionary View A Little Background: Natural Selection and Genetics Comparative Cognition Evolutionary Psychology Evaluating Evolutionary Psychology Chapter 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 Chapter 10: The Emotional Approach: Mind as Emotion What Is Emotion? Theories of Emotion Basic Emotions Emotions, Evolution, and Psychological Disorders Emotions and Neuroscience Hot and Cold: Emotion-Cognition Interactions Emotions and Artificial Intelligence: Affective Computing Chapter 11: The Social Approach: Mind as Society Social Cognition Social Cognitive Neuroscience Topics in Social Cognitive Neuroscience Is Social Cognitive Neuroscience Special? Advantages of the Social Cognitive Neuroscience Approach Theory of Mind Other Social Cognitive Disorders Attitudes Impressions Attribution Stereotypes Prejudice Chapter 12: The Artificial Intelligence Approach I: Mind as Machine Cognitive Science and Artificial Intelligence Historical Precursors Defining AI Doctrinal Arguments Turing's Critical Legacy Practical AI Fuzzy Thinking - the legacy of Lotfi Zadeh The Contentious Debate and AI Evolution The Neural Net Model and its Capabilities The New Millennium: Cognitive Computing (Is it possible to "build" a brain?) Chapter 13: The Artificial Intelligence Approach II: Embodiments and Robotics The Intelligent Agent Paradigm Emerging Developments Chapter 14: Conclusion: Where We Go From Here The Benefits of Cognitive Science Issues in Cognitive Science The Dynamical Systems Approach Dynamical Representation Dynamical Versus Classical Cognitive Science Evaluating the Dynamical Perspective Integrating Cognitive Science The Future
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SAGE Publications Inc
970 gr
231 mm
187 mm
05, U
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Jay Friedenberg is Professor of the Psychology Department at Manhattan College, where he directs the Cognitive Science Program. He is interested in both vision and the philosophy of mind. He teaches courses in physiological psychology, cognition and learning, sensation and perception, and artificial intelligence and robotics. He has published several articles on visual estimation of center of mass. His current research projects focus on the aesthetics of geometrical shapes. He has published books on artificial intelligence, dynamical systems theory, and psychology. He is a member of the International Association of Empirical Aesthetics, the Eastern Psychological Association, the Vision Science Society, the Psychonomic Society, and Phi Beta Kappa. He obtained his PhD in cognitive psychology in 1995 at the University of Virginia. Gordon Silverman is Professor Emeritus of Electrical and Computer Engineering at Manhattan College. His professional career spans more than 55 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. His current research interests include telemedicine, rehabilitation medicine, artificial intelligence, and biomedical instrumentation and modeling. He holds engineering degrees from Columbia University and received a PhD in system science from New York University Polytechnic School of Engineering in 1972.