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.

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).