ESKAPE/CF: a knowledge acquisition tool for expert systems using cognitive feedback

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Author
Connor, James W.
Date
1991-03Advisor
Sengupta, Kishore
Second Reader
Bui, Tung
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Show full item recordAbstract
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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