Abstract
Computational theories of classical conditioning are theories whose propositions are stated as mathematical relationships. From such propositions one can compute, that is to say, deduce, presumed consequences for conditioned responding in circumstances addressed by the theory. This chapter is an attempt to roughly categorize and briefly summarize the major computational theories that have been developed to understand behavior in classical conditioning. It is organized around the essential ideas about conditioning that the various theories embrace. This chapter is not intended to provide a relative evaluation of the theories mentioned; to do so is considerably beyond the scope of what can be accomplished in the space available. Data are mentioned and judgments made, but only to provide understanding of the inspiration for the different models.
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Brandon, S.E., Vogel, E.H., Wagner, A.R. (2002). Computational Theories of Classical Conditioning. In: Moore, J.W. (eds) A Neuroscientist’s Guide to Classical Conditioning. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8558-3_7
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