{"pk":26953,"title":"Evidence for the size principle in semantic and perceptual domains","subtitle":null,"abstract":"Shepard’s Universal Law of Generalization offered a com-pelling case for the first physics-like law in cognitive sciencethat should hold for all intelligent agents in the universe. Shep-ard’s account is based on a rational Bayesian model of general-ization, providing an answer to the question of why such a lawshould emerge. Extending this account to explain how humansuse multiple examples to make better generalizations requiresan additional assumption, called the size principle: hypothesesthat pick out fewer objects should make a larger contributionto generalization. The degree to which this principle warrantssimilarly law-like status is far from conclusive. Typically, eval-uating this principle has not been straightforward, requiringadditional assumptions. We present a new method for evaluat-ing the size principle that is more direct, and apply this methodto a diverse array of datasets. Our results provide support forthe broad applicability of the size principle.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"size principle; generalization; similarity; percep-tion"}],"section":"Talks: Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/1zp2h7cj","frozenauthors":[{"first_name":"Joshua","middle_name":"C.","last_name":"Peterson","name_suffix":"","institution":"University of California, Berkeley","department":""},{"first_name":"Thomas","middle_name":"L.","last_name":"Griffiths","name_suffix":"","institution":"University of California, Berkeley","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2017-01-01T21:00:00+03:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26953/galley/16589/download/"}]}