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https://hdl.handle.net/2440/55320
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Type: | Journal article |
Title: | Learning overhypotheses with hierarchical Bayesian models |
Author: | Kemp, C. Perfors, A. Tenenbaum, J. |
Citation: | Developmental Science, 2007; 10(3):307-321 |
Publisher: | Wiley-Blackwell Publishing |
Issue Date: | 2007 |
ISSN: | 1363-755X 1467-7687 |
Statement of Responsibility: | Charles Kemp, Amy Perfors and Joshua B. Tenenbaum |
Abstract: | 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. |
Keywords: | Humans Bayes Theorem Language Development Cognition Verbal Learning Concept Formation Models, Psychological Generalization, Psychological |
DOI: | 10.1111/j.1467-7687.2007.00585.x |
Published version: | http://dx.doi.org/10.1111/j.1467-7687.2007.00585.x |
Appears in Collections: | Aurora harvest 5 Psychology publications |
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