{"pk":24604,"title":"Bias in Belief Updating: Combining the Bayesian Sampler with Heuristics","subtitle":null,"abstract":"People systematically deviate from the rational Bayesian updating of beliefs, as notably evidenced by conservatism and base-rate neglect. The primary cognitive models that explain these biases include simple heuristics (Woike et al., 2023, https://doi.org/10.1016/j.cogpsych.2023.101564) and stochastic sampling approximations of the Bayesian solution, like the Bayesian Sampler (Zhu et al., 2020, https://doi.org/10.1037/rev0000190). However, neither type of explanation appears entirely complete, as the data fall between the two; only about half of participants' responses align with heuristics. Could these results be explained by a new class of models that blend heuristics with Bayesian models? We test both simple mixtures of heuristics and the Bayesian Sampler, as well as a hybrid model in which heuristics are used to set a prior that improves estimates based on stochastic samples. Our analysis indicates that neither heuristics nor the Bayesian Sampler alone are sufficient to explain the data.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Psychology; Behavioral Science; Decision making; Bayesian modeling; Computational Modeling"}],"section":"Abstracts","is_remote":true,"remote_url":"https://escholarship.org/uc/item/5142b5v1","frozenauthors":[{"first_name":"Yitong","middle_name":"","last_name":"Lin","name_suffix":"","institution":"University of Warwick","department":""},{"first_name":"Jian-Qiao","middle_name":"","last_name":"Zhu","name_suffix":"","institution":"Princeton University","department":""},{"first_name":"Adam","middle_name":"","last_name":"Sanborn","name_suffix":"","institution":"University of Warwick","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2024-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/24604/galley/17770/download/"}]}