Subjective Bayesian Methods for Rule-Based Inference Systems

Abstract

The general problem of drawing inferences from uncertain or incomplete evidence has invited a variety of technical approaches, some mathematically rigorous and some largely informal and intuitive. Most current inference systems in artificial intelligence have emphasized intuitive methods because the absence of adequate statistical samples forces a reliance on the subjective judgment of human experts. In this paper, the authors describe a subjective Bayesian inference method that realizes some of the advantages of both formal and informal approaches. Of particular interest are the modifications needed to deal with the inconsistencies usually found in collections of subjective statements.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1976
Accession Number
ADA458708

Entities

People

  • Nils J. Nilsson
  • Peter E. Hart
  • Richard O. Duda

Organizations

  • SRI International

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Availability
  • Bayesian Inference
  • Classification
  • Contracts
  • Data Science
  • Information Operations
  • Information Science
  • Instructions
  • Judgment
  • Monitoring
  • Security
  • Standards
  • Statistical Samples

Readers

  • Economics
  • Statistical inference.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy