{"pk":30101,"title":"Order Effects in One-shot Causal Generalization","subtitle":null,"abstract":"We introduce a novel task exploring how people make causal generalizations over the abstract features of the objectsinvolved in a causal interaction. Specifically, we investigate how people generalize from a single observation of two sim-ple objects in which one (the agent, or cause) interacts with another (the recipient, or effect) resulting in some featurechange(s). In line with recent demonstrations of human strength in few-shot concept learning, we find strong and sys-tematic patterns of generalizations that are well explained by a Bayesian inference model favoring simpler causal rules.However, we also identify a clear order effect depending on what order generalizations are made. To capture the observedpatterns, we develop a causal hypothesis generation model that takes peoples natural generalization tendency and the ordereffect into consideration, and outperforms plain Bayesian inference both in computational efficiency and in match to thebehavioral data.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Poster Session 3","is_remote":true,"remote_url":"https://escholarship.org/uc/item/7974408p","frozenauthors":[{"first_name":"Bonan","middle_name":"","last_name":"Zhao","name_suffix":"","institution":"The University of Edinburgh","department":""},{"first_name":"Neil","middle_name":"","last_name":"Bramley","name_suffix":"","institution":"The 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/30101/galley/19955/download/"}]}