Images and inference

It is frequently asked whether imagery differs in a fundamental way from other forms of knowledge representation, specifically the predicative forms employed in artificial intelligence programs. Frequently suggested distinctions are pictorial versus descriptional, and analog versus digital. This paper argues that these distinctions are not central in understanding the role of imagery in cognition, and moreover do not correctly capture the difference between visual perception and language. A distinction is proposed between the representation of images, on the one hand, and a calculus-plus-proof-procedure form of knowledge representation on the other. This distinction is not based upon differences in expressive power or form, but rather is based upon a distinction between how these two representations function, specifically how they are used to make inferences. On this view, an important functional role of imagery is to provide a non-proof-procedural method for inference, using a constraint satisfaction mechanism. Images, even the limited class of images here called diagrams, support inference in a way that is distinct from the way predicative representations support inference. This analysis offers an approach to solving the "frame problem" of cognitive science.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27193/1/0000196.pd