{"pk":30059,"title":"What you didn’t see:Prevention and generation in continuous time causal induction","subtitle":null,"abstract":"How do people use temporal information to make causal judg-ments? A number of studies have investigated the role of timein inferring generative causal structure, while few have exam-ined prevention. Here, we focus on a challenging task in whichparticipants learn the structure of several causal “devices” bywatching the devices’ patterns of activation over time. Eachdevice potentially includes both generative (producing an acti-vation of its effect) and preventative (blocking any effect acti-vations within a short time window) causal relationships. Weexamine judgment patterns through the lens of a normativemodel which incorporates actual causation with considerationsof prevention. We contrast this with a more computationallytractable feature-based approximation. Participants’ perfor-mance was substantially above chance in all conditions. Themajority of participants’ causal judgments were best fit by thefeature-based approximation based on delay and count heuris-tic cues.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"causal learning; time; prevention; structure induc-tion; Bayesian modelling"}],"section":"Poster Session 3","is_remote":true,"remote_url":"https://escholarship.org/uc/item/9pg363n6","frozenauthors":[{"first_name":"Tianwei","middle_name":"","last_name":"Gong","name_suffix":"","institution":"University of Edinburgh","department":""},{"first_name":"Neil","middle_name":"R.","last_name":"Bramley","name_suffix":"","institution":"University of Edinburgh","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2020-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/30059/galley/19913/download/"}]}