Simulating Rule-Based Systems

Abstract

The purpose of this thesis is to develop a methodology for evaluating the performance of rule-based systems (RBSs) using a simulation approach. A numerical scheme is used for knowledge representation; facts are represented by integer numbers and the rules and data memories are represented by matrices. The numeric representation can be handled by simplified algorithms that simulate the function of different types of inference engines. Six types of forward-chaining inference engines that vary according to the conflict resolution strategy and the implementation of filters are simulated and compared. The number of match- tests of the left-hand side of the rules against the data memory is used as a measure of performance to estimate the relative matching effort for each inference engine. Also, a methodology to reduce the matching effort of RBS by changing the order of the facts in the left-hand side or changing the order of the rules is described. Keywords: Expert systems, Computer programs.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1988
Accession Number
ADA202563

Entities

People

  • Nizar M. Mahaba

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Algorithms
  • Application Software
  • Artificial Intelligence
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Expert Systems
  • Inference Engines
  • Information Systems
  • Lisp Programming Language
  • Reasoning
  • Rule Based Systems
  • Simulations
  • Simulators

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Artificial Intelligence
  • Human-Computer Interaction (HCI).

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference