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) About the Author: Michael R. W. Dawson is a member of the Department of Psychology and the Biological Computation Project at the University of Alberta, Canada. He is the author of Understanding Cognitive Science (Blackwell, 1998) and Minds and Machines (Blackwell, 2004).