{"pk":32736,"title":"Rule learning by Habituation can be Simulated in Neural Networks","subtitle":null,"abstract":"Contrary to a recent claim that neural network models are unable to account for data on infant habituation to artificial language sentences, the present simulations show successful coverage with cascade-correlation networks using analog encoding. The results demonstrate that a symbolic rule-based account is not required by the infant data.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Long Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/94b313rf","frozenauthors":[{"first_name":"Thomas","middle_name":"R.","last_name":"Shultz","name_suffix":"","institution":"Department of Psychology; McGill University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1999-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/32736/galley/23798/download/"}]}