On Modeling of If-Then Rules for Probabilistic Inference

Abstract

We identify various situations in probabilistic intelligent systems in which conditionals (rules) as mathematical entities as well as their conditional logic operations are needed. In discussing Bayesian updating procedure and belief function construction, we provide a new method for modeling if...then rules as Boolean elements, and yet, compatible with conditional probability quantifications.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1993
Accession Number
ADA262789

Entities

People

  • Hung T. Nguyen
  • I. R. Goodman

Organizations

  • Naval Command, Control and Ocean Surveillance Center

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Applied Computer Science
  • Artificial Intelligence
  • Boolean Algebra
  • Computer Science
  • Expert Systems
  • Fuzzy Logic
  • Fuzzy Sets
  • Intelligent Systems
  • Language
  • Logic
  • Natural Languages
  • New Mexico
  • Ocean Surveillance
  • Probability
  • Random Variables
  • Rule Based Systems

Readers

  • Artificial Intelligence

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference