{"pk":31246,"title":"Direct, Incremental Learning of Fuzzy Propositions","subtitle":null,"abstract":"To enable the gradual learning of symbolic representations, a new fuzzy logical operator is developed that supports the expression of negation to degrees. As a result, simple fuzzy propositions become instantiable in a feedforward network having multiplicative nodes and tunable negation links. A backpropagation learning procedure has been straightforwardly developed for such a network and applied to effect the direct, incremental learning of fuzzy propositions in a natural and satisfying manner. Some results of this approach and comparisons to related approaches are discussed as well as directions for further extension.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Talks","is_remote":true,"remote_url":"https://escholarship.org/uc/item/8kh9c3tb","frozenauthors":[{"first_name":"Gregg","middle_name":"C.","last_name":"Oden","name_suffix":"","institution":"University of Iowa","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1992-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/31246/galley/22315/download/"}]}