Authors
Nina Poth
Ruhr-Universität Bochum
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.
Keywords Generalisation, Similarity, Bayesian inference, Unification, Mutual informational relevance
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DOI 10.1007/s13164-022-00613-5
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References found in this work BETA

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.

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