{"pk":26516,"title":"Episodic memory as a prerequisite for online updates of model structure","subtitle":null,"abstract":"Human learning in complex environments critically dependson the ability to perform model selection, that is to assess com-peting hypotheses about the structure of the environment. Im-portantly, information is accumulated continuously, which ne-cessitates an online process for model selection. While modelselection in human learning has been explored extensively, it isunclear how memory systems support learning in an online set-ting. We formulate a semantic learner and demonstrate that on-line learning on open model spaces results in a delicate choicebetween either tracking a possibly infinite number of compet-ing models or retaining experiences in an intact form. Sincenone of these choices is feasible for a bounded-resource mem-ory system, we propose an episodic learner that retains an op-timised subset of experiences in addition to semantic memory.On a simple model system we demonstrate that this norma-tive theory of episodic memory can effectively circumvent thechallenge of online model selection.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"episodic memory; semantic memory; onlinemodel selection; Bayesian modeling; bounded-resource-rationality"}],"section":"Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/9rz56360","frozenauthors":[{"first_name":"David","middle_name":"G.","last_name":"Nagy","name_suffix":"","institution":"Wigner Research Centre for Physics","department":""},{"first_name":"Gergo","middle_name":"","last_name":"Orban","name_suffix":"","institution":"Eotvos Lorand University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2016-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26516/galley/16152/download/"}]}