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dc.contributor.authorUllman, Tomer D
dc.contributor.authorTenenbaum, Joshua B
dc.date.accessioned2021-12-07T19:10:30Z
dc.date.available2021-12-07T19:10:30Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/138358
dc.description.abstractA Bayesian framework helps address, in computational terms, what knowledge children start with and how they construct and adapt models of the world during childhood. Within this framework, inference over hierarchies of probabilistic generative programs in particular offers a normative and descriptive account of children's model building. We consider two classic settings in which cognitive development has been framed as model building: ( a) core knowledge in infancy and ( b) the child as scientist. We interpret learning in both of these settings as resource-constrained, hierarchical Bayesian program induction with different primitives and constraints. We examine what mechanisms children could use to meet the algorithmic challenges of navigating large spaces of potential models, in particular the proposal of the child as hacker and how it might be realized by drawing on recent computational advances. We also discuss prospects for a unifying account of model building across scientific theories and intuitive theories, and in biological and cultural evolution more generally.en_US
dc.language.isoen
dc.publisherAnnual Reviewsen_US
dc.relation.isversionof10.1146/ANNUREV-DEVPSYCH-121318-084833en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePsyArXiven_US
dc.titleBayesian Models of Conceptual Development: Learning as Building Models of the Worlden_US
dc.typeArticleen_US
dc.identifier.citationUllman, Tomer D and Tenenbaum, Joshua B. 2020. "Bayesian Models of Conceptual Development: Learning as Building Models of the World." Annual Review of Developmental Psychology, 2 (1).
dc.relation.journalAnnual Review of Developmental Psychologyen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-12-07T18:56:35Z
dspace.orderedauthorsUllman, TD; Tenenbaum, JBen_US
dspace.date.submission2021-12-07T18:56:36Z
mit.journal.volume2en_US
mit.journal.issue1en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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