---
title: "An Inference Technique for Integrating Knowledge from Disparate Sources"
authors:
  - "Thomas D. Garvey"
  - "John D. Lowrance"
  - "Martin A. Fischler"
doi: ""
url: "https://ijcai.org/proceedings/1981/63"
pdf: "https://ijcai.org/proceedings/1981/0063.pdf"
venue: "Proceedings of the Seventh International Joint Conference on Artificial Intelligence"
year: 1981
pages: "319-324"
track: "INFERENCE and REASONING"
keywords:
---

# An Inference Technique for Integrating Knowledge from Disparate Sources

Thomas D. Garvey, John D. Lowrance, Martin A. Fischler

*Proceedings of the Seventh International Joint Conference on Artificial Intelligence*, pages 319-324.

## 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.