Inductive inference based on probability and similarity

We advance a theory of inductive inference designed to predict the conditional probability that certain natural categories satisfy a given predicate given that others do (or do not). A key component of the theory is the similarity of the categories to one another. We measure such similarities in terms of the overlap of metabolic activity in voxels of various posterior regions of the brain in response to viewing instances of the category. The theory and similarity measure are tested against averaged probability judgments elicited from a separate group of subjects. Fruit serve as categories in the present experiment; results are compared to earlier work with mammals.
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