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https://hdl.handle.net/2440/55320
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dc.contributor.author | Kemp, C. | - |
dc.contributor.author | Perfors, A. | - |
dc.contributor.author | Tenenbaum, J. | - |
dc.date.issued | 2007 | - |
dc.identifier.citation | Developmental Science, 2007; 10(3):307-321 | - |
dc.identifier.issn | 1363-755X | - |
dc.identifier.issn | 1467-7687 | - |
dc.identifier.uri | http://hdl.handle.net/2440/55320 | - |
dc.description.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. | - |
dc.description.statementofresponsibility | Charles Kemp, Amy Perfors and Joshua B. Tenenbaum | - |
dc.language.iso | en | - |
dc.publisher | Wiley-Blackwell Publishing | - |
dc.source.uri | http://dx.doi.org/10.1111/j.1467-7687.2007.00585.x | - |
dc.subject | Humans | - |
dc.subject | Bayes Theorem | - |
dc.subject | Language Development | - |
dc.subject | Cognition | - |
dc.subject | Verbal Learning | - |
dc.subject | Concept Formation | - |
dc.subject | Models, Psychological | - |
dc.subject | Generalization, Psychological | - |
dc.title | Learning overhypotheses with hierarchical Bayesian models | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1111/j.1467-7687.2007.00585.x | - |
pubs.publication-status | Published | - |
Appears in Collections: | Aurora harvest 5 Psychology publications |
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