{"pk":28651,"title":"A computational model of feature formation, event prediction, and attentionswitching","subtitle":null,"abstract":"In this paper we present a model of three central aspects ofprobabilistic cognition: event prediction, feature formation,and attention allocation. While most models of probabilisticreasoning take a parameter estimation and error minimisationapproach (sometimes referred to as ‘predictive coding’, and of-ten described in terms of Bayesian updating), our model takesa contrasting frequentist hypothesis-testing approach. Thischoice is motivated by a series of recent results suggesting thatpeople’s probabilistic reasoning follows frequentist probabilitytheory. In simulation tests we demonstrate that this frequentistmodel, in which predictive features are formed by a process ofnull hypothesis significance testing, can give a successful ac-count of event prediction and attentional switching behaviour.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Papers with Poster Presentations","is_remote":true,"remote_url":"https://escholarship.org/uc/item/6s16n7qn","frozenauthors":[{"first_name":"Eman","middle_name":"","last_name":"Awad","name_suffix":"","institution":"University College Dublin","department":""},{"first_name":"Fintan","middle_name":"","last_name":"Costello","name_suffix":"","institution":"University College Dublin","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/28651/galley/18522/download/"}]}