Title

Learning overhypotheses with hierarchical Bayesian models.

Date of Original Version

5-1-2007

Type

Article

PubMed ID

17444972

Abstract or Description

Inductive learning is impossible without overhypotheses, or constraints on the hypotheses considered by the learner. Some of these overhypotheses must be innate, but we suggest that hierarchical Bayesian models can help to explain how the rest are acquired. To illustrate this claim, we develop models that acquire two kinds of overhypotheses--overhypotheses about feature variability (e.g. the shape bias in word learning) and overhypotheses about the grouping of categories into ontological kinds like objects and substances.

DOI

10.1111/j.1467-7687.2007.00585.x

 

Published In

Developmental Science, 10, 3, 307-321.