Refining the Bayesian Approach to Unifying Generalisation

Review of Philosophy and Psychology 14 (3):877-907 (2023)
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Abstract

Tenenbaum and Griffiths (Behavioral and Brain Sciences 24(4):629–640, 2001) have proposed that their Bayesian model of generalisation unifies Shepard’s (Science 237(4820): 1317–1323, 1987) and Tversky’s (Psychological Review 84(4): 327–352, 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.

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Author's Profile

Nina Poth
Humboldt University, Berlin

References found in this work

Explanation and scientific understanding.Michael Friedman - 1974 - Journal of Philosophy 71 (1):5-19.
Features of similarity.Amos Tversky - 1977 - Psychological Review 84 (4):327-352.
Bayesian Cognitive Science, Unification, and Explanation.Stephan Hartmann & Matteo Colombo - 2017 - British Journal for the Philosophy of Science 68 (2).
Conceptual Spaces: The Geometry of Thought.Peter Gärdenfors - 2000 - Tijdschrift Voor Filosofie 64 (1):180-181.

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