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{ "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": "2017-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26953/galley/16589/download/" } ] }