Qualitative Reasoning in an Expert System Framework

Expert systems typically utilize a declarative and uniform knowledge representation. The approach offers many operational advantages (e.g., a simple control structure), but is limited to expressing an expert's surface level knowledge in the form of pattern-decision pairs. The computer should have access to 'deeper' knowledge if it is to understand and justify its planning actions. Consider a domain where knowledge in the form of equations and algorithms is computationally too complex for use by the human practitioner. How should mathematical knowledge be represented to aid in the improvement and justification of plans? In the task domain of this research, enroute air traffic control, heuristically generated plans are justified by applying qualitative reasoning to aircraft performance equations. Equations are represented in a semantic network where nodes represent variables and links represent dependent variable influences.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Cross, Stephen Edward

• Engineering, Electronics and Electrical

Identifier

(UMI)AAI8409903

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/69273