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{ "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/" } ] }