Knowledge Acquisition for an Expert System in the Air Force Civil Engineering Operations Branch

Abstract

Expert systems are being developed in several industries throughout the world. The key element in these systems is gathering the knowledge. The purpose of this study was to establish procedures for gathering this knowledge in Air Force Civil Engineering. As a test of the procedures, an expert system was created to solve two common semistructured decisions in civil engineering operations. These two decisions involved approving or disapproving a work request, and then determining the appropriate method of accomplishing approved work. The primary emphasis of the study was on developing and exercising a specific methodology for extracting the knowledge. Several journals and periodicals were reviewed to determine what makes up an expert system and how a knowledge base is developed. The methodology of knowledge acquisition involved five general steps. The steps included knowledge familiarization, expert selection, interviewing, knowledge representation, and finally automation. Each step is clearly defined in this thesis. The knowledge base was automated using the expert shell VP-Expert by Paperback Software. The knowledge acquisition steps used in this research and the automated knowledge base are launching platforms for future research involving expert systems in Air Force Civil Engineering. Recommendations for further research are provided within this thesis. Theses.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1988
Accession Number
ADA201625

Entities

People

  • Randy D. Eide

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Artificial Intelligence
  • Civil Engineering
  • Computer Programming
  • Computer Programs
  • Computers
  • Contracts
  • Databases
  • Engineering
  • Engineers
  • Environment
  • Environmental Engineering
  • Expert Systems
  • Inference Engines
  • Logistics
  • Materials

Readers

  • Artificial Intelligence
  • Government and Public Administration Law.
  • Software Engineering