Description
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).
