{"type":"ScholarlyArticle","title":"Representing Diagnostic Knowledge for Probabilistic Horn Abduction","authors":[{"name":"David Poole","slug":"david-poole","given":"David","family":"Poole","affiliation":""}],"abstract":"This paper presents a simple logical framework for abduction , with probabilities associated with hypotheses. The language is an extension to pure Prolog, and it has straight-forward implementations using branch and bound search with either logic-programming technology or ATMS technology. The main focus of this paper is arguing for a form of representational adequacy of this very simple system for diagnostic reasoning. It is shown how it can represent model-based knowledge, with and without faults, and with and without non-intermittency assumptions. It is also shown how this representation can represent any probabilistic knowledge representable in a Bayesian belief network.","doi":null,"url":"https://ijcai.org/proceedings/1991/166","pdf":"https://ijcai.org/proceedings/1991/0166.pdf","markdown":"https://ijcai.org/proceedings/1991/166.md","bibtex":"https://ijcai.org/proceedings/1991/bibtex/166","volume":{"slug":"1991","title":"Proceedings of the Twelfth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1991","url":"https://ijcai.org/proceedings/1991/","year":1991,"location":"Sydney, New South Wales, Australia","dates":"24-30 August 1991","editors":"John Mylopoulos and Ray Reiter","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Qualitative Reasoning","track":"Qualitative Reasoning","number":166,"pages":{"first":1129,"last":1136},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}