{"pk":28772,"title":"Exploring the Representation of Linear Functions","subtitle":null,"abstract":"Function learning research has highlighted the importance ofhuman inductive biases that facilitate long-range extrapola-tions. However, most previous research is focused on aggre-gate errors or single-criterion extrapolations. Thus, little isknown about the underlying psychological space in which con-tinuous relationships are represented. We ask whether peoplecan learn the distributional properties of new classes of rela-tionships, using Markov Chain Monte Carlo with People, andfind that (1) people are able to track not just the expected pa-rameters of a linear function, but information about the vari-ability of functions in a specific context and (2) in many casesthese spaces over parameters exhibit multiple modes.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Generalization"},{"word":"Function learning"},{"word":"Representation"}],"section":"Papers with Poster Presentations","is_remote":true,"remote_url":"https://escholarship.org/uc/item/6ts2b90h","frozenauthors":[{"first_name":"Pablo","middle_name":"","last_name":"Le ́on-Villagr ́a","name_suffix":"","institution":"University of Edinburgh","department":""},{"first_name":"Verena","middle_name":"S.","last_name":"Klar","name_suffix":"","institution":"University of Edinburgh","department":""},{"first_name":"Adam","middle_name":"N.","last_name":"Sanborn2","name_suffix":"","institution":"University of Warwick","department":""},{"first_name":"Christopher","middle_name":"G.","last_name":"Lucas","name_suffix":"","institution":"University of Edinburgh","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2019-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/28772/galley/18643/download/"}]}