ESKAPE/CF: A Knowledge Acquisition Tool for Expert Systems Using Cognitive Feedback

Abstract

The major bottleneck in the construction of expert systems is the time-consuming process of acquiring knowledge from experts. Automated knowledge acquisition tools have demonstrated the ability to reduce the time required to construct expert system knowledge bases and are supported by both knowledge engineers and experts. However, due to limitations in their underlying psychological paradigms, existing tools may not be well-suited to extracting semantic or procedural knowledge from an expert. This thesis designs and implements an Expert System Knowledge Acquisition and Policy Evaluation tool using Cognitive Feedback (ESKAPE/CF), based on Lens model techniques which have demonstrated effectiveness in capturing policy knowledge. The system is designed to be used interactively by an expert to reduce the historically lengthy interactions with a knowledge engineer. Additionally, the use of cognitive feedback techniques should enable the system to capture expertise that has heretofore been unobtainable by existing knowledge acquisition tools.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1991
Accession Number
ADA241815

Entities

People

  • James W. Connor Jr

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Applied Psychology
  • Artificial Intelligence
  • Cognitive Science
  • Computers
  • Control Panels
  • Engineering
  • Engineers
  • Expert Systems
  • Feedback
  • Information Processing
  • Information Systems
  • Judgment
  • Knowledge Based Systems
  • Psychology
  • Test And Evaluation
  • United States
  • United States Government

Readers

  • Artificial Intelligence
  • Software Engineering.
  • Systems Analysis and Design