Behavioral and Brain Sciences



Short Communication

Developing a domain-general framework for cognition: What is the best approach?


James L. McClelland a1, David C. Plaut a1, Stephen J. Gotts a2 and Tiago V. Maia a3
a1 Department of Psychology and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213 jlm@cnbc.cmu.edu plaut@cmu.edu http://www.cnbc.cmu.edu/~jlm http://www.cnbc.cmu.edu/~plaut
a2 Department of Psychology and Center for the Neural Basis of Cognition, Carnegie Mellon University, and Laboratory of Neuropsychology, NIMH/NIH, Bethesda, MD 20892 gotts@nih.gov http://www.cnbc.cmu.edu/~gotts
a3 Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213 tmaia@cmu.edu http://www.cnbc.cmu.edu/~tmaia

Abstract

We share with Anderson & Lebiere (A&L) (and with Newell before them) the goal of developing a domain-general framework for modeling cognition, and we take seriously the issue of evaluation criteria. We advocate a more focused approach than the one reflected in Newell's criteria, based on analysis of failures as well as successes of models brought into close contact with experimental data. A&L attribute the shortcomings of our parallel-distributed processing framework to a failure to acknowledge a symbolic level of thought. Our framework does acknowledge a symbolic level, contrary to their claim. What we deny is that the symbolic level is the level at which the principles of cognitive processing should be formulated. Models cast at a symbolic level are sometimes useful as high-level approximations of the underlying mechanisms of thought. The adequacy of this approximation will continue to increase as symbolic modelers continue to incorporate principles of parallel distributed processing.