A Measure-Free Approach to Conditioning

Abstract

In an earlier paper, a new theory of measure-free conditional objects was presented. In this paper, emphasis is placed upon the motivation of the theory. The central part of this motivation is established through an example involving a knowledge based system. In order to evaluate combination of evidence for this system, using observed data, auxiliary attribute and diagnosis variables, and inference rules connecting them, one must first choose an appropriate algebraic logic description pair (ALDP): a formal language or syntax followed by a compatible logic or semantic evaluation (or model). Three common choices-for this highly non-unique choice-are briefly discussed, the logics being Classical Logic, Fuzzy Logic, and Probability Logic. In all three, the key operator representing implication for the inference rules is interpreted as the often-used disjunction of a negation for any events a, b.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1987
Accession Number
ADA240417

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  • I. R. Goodman

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  • C4I

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Boolean Algebra
  • Calculus
  • Data Fusion
  • Formal Languages
  • Fuzzy Logic
  • Identification
  • Information Processing
  • Knowledge Based Systems
  • Language
  • Logic
  • Motivation
  • New York
  • Social Sciences
  • Test And Evaluation
  • Universities

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  • Artificial Intelligence

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Translation