Computing Probability Masses in Rule-Based Systems

Abstract

This report describes a method of computing confidences in rule-based inference systems by using the Dempster-Shafter theory. The theory is applicable to tactical decision problems which can be formulated in terms of sets of exhaustive and mutually exclusive propositions. Dempster's combining procedure, a generalization of Bayesian inference, can be used to combine probability mass assignments supplied by independent bodies of evidence. This report describes the use of Dempster's combining method and Shafer's representation framework in rule-based inference systems. It is shown that many kinds of data fusion problems can be represented in a way such that the constraints are met. Although computational problems remain to be solved, the theory should provide a versatile and consistent way of combining confidences for a large class of inferencing problems. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 08, 1982
Accession Number
ADA125509

Entities

People

  • R. A. Dillard

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Ground and Sea Platforms
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Inference
  • Boats
  • Classification
  • Command And Control
  • Computational Science
  • Computations
  • Data Fusion
  • Detection
  • Distribution Functions
  • Information Processing
  • Information Science
  • Military Operations
  • Patrol Craft
  • Radar
  • Rule Based Systems
  • Security

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms