Refining the Bayesian Approach to Unifying Generalisation

Abstract

AbstractTenenbaum and Griffiths (Behavioral and Brain Sciences24(4):629–640, 2001) have proposed that their Bayesian model of generalisation unifies Shepard’s (Science237(4820): 1317–1323, 1987) and Tversky’s (Psychological Review84(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.