{"pk":26499,"title":"Inferring priors in compositional cognitive models","subtitle":null,"abstract":"We apply Bayesian data analysis to a structured cognitivemodel in order to determine the priors that support humangeneralizations in a simple concept learning task. We mod-eled 250,000 ratings in a “number game” experiment wheresubjects took examples of a numbers produced by a program(e.g. 4, 16, 32) and rated how likely other numbers (e.g. 8vs. 9) would be to be generated. This paper develops a dataanalysis technique for a family of compositional “Language ofThought” (LOT) models which permits discovery of subjects’prior probability of mental operations (e.g. addition, multi-plication, etc.) in this domain. Our results reveal high cor-relations between model mean predictions and subject gener-alizations, but with some qualitative mismatch for a stronglycompositional prior.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Concepts and categories; learning; Bayesian mod-eling; machine learning"}],"section":"Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/43s5z8jj","frozenauthors":[{"first_name":"Eric","middle_name":"J.","last_name":"Bigelow","name_suffix":"","institution":"University of Rochester","department":""},{"first_name":"Steven","middle_name":"T.","last_name":"Piantadosi","name_suffix":"","institution":"University of Rochester","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2016-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26499/galley/16135/download/"}]}