Refining the Bayesian Approach to Unifying Generalisation

Review of Philosophy and Psychology (3):1-31 (2022)
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Abstract

Tenenbaum and Griffiths (2001) have proposed that their Bayesian model of generalisation unifies Shepard’s (1987) and Tversky’s (1977) similarity-based explanations of two distinct patterns of generalisation behaviours by reconciling them under a single coherent task analysis. I argue that this proposal needs refinement: instead of unifying the heterogeneous notion of psychological similarity, the Bayesian approach unifies generalisation by rendering the distinct patterns of behaviours informationally relevant. I suggest that generalisation as a Bayesian inference should be seen as a complement to, instead of a replacement of, similarity-based explanations. Furthermore, I show that the unificatory powers of the Bayesian model of generalisation can contribute to the selection of one of these models of psychological similarity.

Other Versions

reprint Poth, Nina (2023) "Refining the Bayesian Approach to Unifying Generalisation". Review of Philosophy and Psychology 14(3):877-907

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