{"type":"ScholarlyArticle","title":"A Framework for Heuristic Reasoning About Uncertainty","authors":[{"name":"Paul R. Cohen","slug":"paul-r-cohen","given":"Paul R.","family":"Cohen","affiliation":""},{"name":"Milton R. Grinberg","slug":"milton-r-grinberg","given":"Milton R.","family":"Grinberg","affiliation":""}],"abstract":"This paper describes a theory of reason ing about uncertainty, based on a repr es entation of stat e·> of certainty called e nd or $e m ents (see Cohen and Grinberg, 1983, for a more detailed discussion of the theory.) The theory of endor se ments is an alternative to numerical methods for reasoning about uncertainty, such as subjective Bayesian methods (Shortliffe and Buchanan, 1975; Duda, Hart, and Nilsson, 1976) and the Shafer· Dempster theory (Shafer, 1976) . The fundamental concern with numerical representations of certainty is that they hide the reasoning that produces them and thus limit one 's reasoning about uncertainty. While numbe rs are easy to propagate over inferences, what the numbers mean is unclear. The theory of endorsements represents the factors that affect certainty and supports multiple strategies for dealing with uncertainty.","doi":null,"url":"https://ijcai.org/proceedings/1983/84","pdf":"https://ijcai.org/proceedings/1983/0084.pdf","markdown":"https://ijcai.org/proceedings/1983/84.md","bibtex":"https://ijcai.org/proceedings/1983/bibtex/84","volume":{"slug":"1983","title":"Proceedings of the Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1983","url":"https://ijcai.org/proceedings/1983/","year":1983,"location":"Karlsruhe, West Germany","dates":"","editors":"Alan Bundy","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Knowledge Representation","track":"Knowledge Representation","number":84,"pages":{"first":355,"last":356},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}