Cognitive science arose in the 1950s when it became apparent that a number of disciplines, including psychology, computer science, linguistics, and philosophy, were fragmenting. Perhaps owing to the field's immediate origins in cybernetics, as well as to the foundational assumption that cognition is information processing, cognitive science initially seemed more unified than psychology. However, as a result of differing interpretations of the foundational assumption and dramatically divergent views of the meaning of the term information processing, three separate schools emerged: classical cognitive science, connectionist cognitive science, and embodied cognitive science. Examples, cases, and research findings taken from the wide range of phenomena studied by cognitive scientists effectively explain and explore the relationship among the three perspectives. Intended to introduce both graduate and senior undergraduate students to the foundations of cognitive science, Mind, Body, World addresses a number of questions currently being asked by those practicing in the field: What are the core assumptions of the three different schools? What are the relationships between these different sets of core assumptions? Is there only one cognitive science, or are there many different cognitive sciences? Giving the schools equal treatment and displaying a broad and deep understanding of the field, Dawson highlights the fundamental tensions and lines of fragmentation that exist among the schools and provides a refreshing and unifying framework for students of cognitive science.

This concise introduction to cognitive science provides undergraduate and graduate students with the theoretical foundations of classical and connectionist cognitive science to explain and teach the underlying unity of the field.

What Is Cognitive Psychology? identifies the theoretical foundations of cognitive psychology—foundations which have received very little attention in modern textbooks. Beginning with the basics of information processing, Michael R. W. Dawson explores what experimental psychologists infer about these processes and considers what scientific explanations are required when we assume cognition is rule-governed symbol manipulation. From these foundations, psychologists can identify the architecture of cognition and better understand its role in debates about its true nature. This volume offers a deeper understanding of cognitive psychology and presents ideas for integrating traditional cognitive psychology with more modern fields like cognitive neuroscience.

Minds and Machines: Connectionism and Psychological Modeling examines different kinds of models and investigates some of the basic properties of connectionism in the context of synthetic psychology, including detailed accounts of how the internal structure of connectionist networks can be interpreted. Introduces connectionist models as tools that are both synthetic and representational and which can be used as the basis for conducting synthetic psychology. Includes distinctively varied account of modeling, historical overview of the synthetic approach, and unique perspectives on connectionism. Investigates basic properties of connectionism in the context of synthetic psychology, including detailed accounts of how the internal structure can be interpreted. Provides supplementary material online at www.bcp.psych.ualberta.ca/~mike/Book2/ which includes free software for conducting connectionist simulations and instructions for building simple robots.

Connectionism is a “hands on” introduction toconnectionist modeling through practical exercises in differenttypes of connectionist architectures. explores three different types of connectionist architectures– distributed associative memory, perceptron, and multilayerperceptron provides a brief overview of each architecture, a detailedintroduction on how to use a program to explore this network, and aseries of practical exercises that are designed to highlight theadvantages, and disadvantages, of each accompanied by a website athttp://www.bcp.psych.ualberta.ca/~mike/Book3/ that includespractice exercises and software, as well as the files and blankexercise sheets required for performing the exercises designed to be used as a stand-alone volume or alongsideMinds and Machines: Connectionism and Psychological Modeling(by Michael R.W. Dawson, Blackwell 2004)

Previously, artificial neural networks have been used to capture only the informal properties of music. However, cognitive scientist Michael Dawson found that by training artificial neural networks to make basic judgments concerning tonal music, such as identifying the tonic of a scale or the quality of a musical chord, the networks revealed formal musical properties that differ dramatically from those typically presented in music theory. For example, where Western music theory identifies twelve distinct notes or pitch-classes, trained artificial neural networks treat notes as if they belong to only three or four pitch-classes, a wildly different interpretation of the components of tonal music. Intended to introduce readers to the use of artificial neural networks in the study of music, this volume contains numerous case studies and research findings that address problems related to identifying scales, keys, classifying musical chords, and learning jazz chord progressions. A detailed analysis of the internal structure of trained networks could yield important contributions to the field of music cognition.

Previously, artificial neural networks have been used to capture only the informal properties of music. However, cognitive scientist Michael Dawson found that by training artificial neural networks to make basic judgments concerning tonal music, such as identifying the tonic of a scale or the quality of a musical chord, the networks revealed formal musical properties that differ dramatically from those typically presented in music theory. For example, where Western music theory identifies twelve distinct notes or pitch-classes, trained artificial neural networks treat notes as if they belong to only three or four pitch-classes, a wildly different interpretation of the components of tonal music. Intended to introduce readers to the use of artificial neural networks in the study of music, this volume contains numerous case studies and research findings that address problems related to identifying scales, keys, classifying musical chords, and learning jazz chord progressions. A detailed analysis of the internal structure of trained networks could yield important contributions to the field of music cognition.

Presents the University of Alberta Cognitive Science Dictionary, which is designed to assist students in learning about the basic concepts of cognitive science. Notes that entries can be found in the index by first letter or a specific term can be searched for in the dictionary. Highlights information on topics such as consciousness, cognitive mapping, cognitive psychology, free recall, intention, Occam's Razor, recognition recall, and working memory.