{"type":"ScholarlyArticle","title":"An Inference Technique for Integrating Knowledge from Disparate Sources","authors":[{"name":"Thomas D. Garvey","slug":"thomas-d-garvey","given":"Thomas D.","family":"Garvey","affiliation":""},{"name":"John D. Lowrance","slug":"john-d-lowrance","given":"John D.","family":"Lowrance","affiliation":""},{"name":"Martin A. Fischler","slug":"martin-a-fischler","given":"Martin A.","family":"Fischler","affiliation":""}],"abstract":"This paper introduces a formal method for integrating knowledge derived from a variely of sources for use in \"perceptual reasoning.\" The formalism is based on the \"evidential propositional calculus,\" a derivative of Shafer's mathematical theory of evidence [4]. It is more general than either a Boolean or Bayesian approach, providing for Boolean and Bayesian inferencing when the appropriate information is available. In this formalism, the likelihood of a proposition A is represented as a subinterval, [s(A),p(A)], of the unit interval, [0,1], The evidential support for proposition A is represented by s(A), while p(A) represents its degree of plausibility; p(A) can also be interpreted as the degree to which one fails to doubt A, p(A) being equal to one minus the evidential support for -A. This paper describes how evidential information, furnished by a knowledge source in the form of a probability \"mass\" distribution, can be converted to this interval representation; how, through a set of inference rules for computing intervals of dependent propositions, this information can be extrapolated from those propositions it directly bears upon, to those it indirectly bears upon; and how multiple bodies of evidential information can be pooled. A sample application of this approach, modeling the operation of a collection of sensors (a particular type of knowledge source), illustrates these techniques.","doi":null,"url":"https://ijcai.org/proceedings/1981/63","pdf":"https://ijcai.org/proceedings/1981/0063.pdf","markdown":"https://ijcai.org/proceedings/1981/63.md","bibtex":"https://ijcai.org/proceedings/1981/bibtex/63","volume":{"slug":"1981","title":"Proceedings of the Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1981","url":"https://ijcai.org/proceedings/1981/","year":1981,"location":"Vancouver, British Columbia, Canada","dates":"24-28 August 1981","editors":"Roger C. Schank","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"INFERENCE and REASONING","track":"INFERENCE and REASONING","number":63,"pages":{"first":319,"last":324},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}