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{ "pk": 29324, "title": "Bayesian Inference Causes Incoherence in Human Probability Judgments", "subtitle": null, "abstract": "Human probability judgements appear systematically biased, in apparent tension with Bayesian models of cognition. Butperhaps the brain does not represent probabilities explicitly, but approximates probabilistic calculations through a processof sampling, as used in computational probabilistic models in statistics. The Bayesian sampling viewpoint provides asimple rational model of probability judgements, which generates biases such as conservatism. The Bayesian samplerprovides a single framework for explaining phenomena associated with diverse biases and heuristics, including availabilityand representativeness. The approach turns out to provide a rational reinterpretation of noise in an important recent modelof probability judgement, the probability theory plus noise model (Costello & Watts, 2014; 2016; 2017; Costello, Watts,& Fisher, 2018), and captures the empirical data supporting this model.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [], "section": "Member Abstracts", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/11g9c4bd", "frozenauthors": [ { "first_name": "Jianqiao", "middle_name": "", "last_name": "Zhu", "name_suffix": "", "institution": "University of Warwick", "department": "" }, { "first_name": "Adam", "middle_name": "", "last_name": "Sanborn", "name_suffix": "", "institution": "University of Warwick", "department": "" }, { "first_name": "Nicholas", "middle_name": "", "last_name": "Chater", "name_suffix": "", "institution": "University of Warwick", "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/29324/galley/19195/download/" } ] }