Models are important tools in psychology used to generate predictions to test the validity of theories. Minds and Machines: Connectionism and Psychological Modeling examines three different kinds of models (models of data, mathematical models, and computer simulations) and discusses a synthetic approach to modeling. Connectionist models are introduced as tools that are both synthetic and representational and that can be used as the basis for conducting synthetic psychology. The book 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. A website of supplementary material is available at www .bcp.psych.ualberta.ca/~mike/Book2/ and includes free software for conducting the connectionist simulations described in the book as well as instructions for building simple robots to illustrate some of the principles of the synthetic approach.
Michael R. W. Dawson is a member of the Department of Psychology and the Biological Computation Project at the University of Alberta, Canada. His primary research interests concern the foundations of cognitive science, learning and representation in connectionist networks, and computational models of motion perception. He is the author of Understanding Cognitive Science (Blackwell Publishers, 1998).