On Foundations of Approximate Reasoning.

Abstract

This paper discusses basic elements required for developing a theory of approximate reasoning which is essential for designing knowledge-based systems which, in turn, can be directly utilized in expert systems. First, formal language will be used as a general framework of analysis. Secondly, semantic evaluation procedures will be developed. Thirdly, the concept of general logical systems will be introduced. Finally, some discussions on uncertainty measures and the problem of admissibility will be discussed. The analysis of knowledge-based systems consists mainly of developing appropriate measures of uncertainty and establishing theories of inference, i.e., systems consisting of axioms, rules and deductions based recursively on them. For example, in statistical systems, semantic evaluations are in the form of probability logic (PL) which supplies the basic operators and relations for the calculus of probability.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1985
Accession Number
ADA240738

Entities

People

  • Hung T. Nguyen

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Connectors
  • Expert Systems
  • Formal Languages
  • Fuzzy Logic
  • Fuzzy Sets
  • Knowledge Based Systems
  • Language
  • Logic
  • New Mexico
  • Probability
  • Reasoning
  • Set Theory
  • Topoi

Readers

  • Artificial Intelligence
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference