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dc.contributor.advisorJoshua B. Tenenbaum.en_US
dc.contributor.authorUllman, Tomer Daviden_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences.en_US
dc.date.accessioned2015-07-17T19:46:34Z
dc.date.available2015-07-17T19:46:34Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/97788
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2015.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 221-236).en_US
dc.description.abstractThis thesis develops formal computational models of intuitive theories, in particular intuitive physics and intuitive psychology, which form the basis of commonsense reasoning. The overarching formal framework is that of hierarchical Bayesian models, which see the mind as having domain-specific hypotheses about how the world works. The work first extends models of intuitive psychology to include higher-level social utilities, arguing against a pure 'classifier' view. Second, the work extends models of intuitive physics by introducing a ontological hierarchy of physics concepts, and examining how well people can reason about novel dynamic displays. I then examine the question of learning intuitive theories in general, arguing that an algorithmic approach based on stochastic search can address several puzzles of learning, including the 'chicken and egg' problem of concept learning. Finally, I argue the need for a joint theory-space for reasoning about intuitive physics and intuitive psychology, and provide such a simplified space in the form of a generative model for a novel domain called Lineland. Taken together, these results forge links between formal modeling, intuitive theories, and cognitive development.en_US
dc.description.statementofresponsibilityby Tomer David Ullman.en_US
dc.format.extent236 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectBrain and Cognitive Sciences.en_US
dc.titleOn the nature and origin of intuitive theories : learning, physics and psychologyen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences.en_US
dc.identifier.oclc911650625en_US


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