{"pk":30310,"title":"What Else Is Wrong With Non-Monotonic Logics? Representational and Informational Shortcomings","subtitle":null,"abstract":"Non-montonic logics have been used recently for a variety of A.I. purposes, including belief revision and default reasoning in question-answering and exper systems. This paper argues that by their nature, such systems dicard information which has a role in human belief systems. In particular, systems which use non-monotonic reasoning lose the distinction between fully justified inferences and reasonable presumptions, in the process losing the ability to record failed expectations as such, an ability which provides a useful measure of salience for A.I. systems.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Paper Session #6","is_remote":true,"remote_url":"https://escholarship.org/uc/item/64s304nw","frozenauthors":[{"first_name":"Jane","middle_name":"Terry","last_name":"Nutter","name_suffix":"","institution":"State University of New York at Buffalo","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1983-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/30310/galley/20164/download/"}]}