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Connectionism is a “hands on” introduction to connectionist modeling through practical exercises in different types of connectionist architectures. explores three different types of connectionist architectures – distributed associative memory, perceptron, and multilayer perceptron provides a brief overview of each architecture, a detailed introduction on how to use a program to explore this network, and a series of practical exercises that are designed to highlight the advantages, and disadvantages, of each accompanied by a website at http://www.bcp.psych.ualberta.ca/~mike/Book3/ that includes practice exercises and software, as well as the files and blank exercise sheets required for performing the exercises designed to be used as a stand-alone volume or alongside Minds and Machines: Connectionism and Psychological Modeling (by Michael R.W. Dawson, Blackwell 2004)

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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.

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