Towards Modeling Human Expertise: An Empirical Case Study

Rainer Knauf, Ilmenau Technical University; Setsuo Tsuruta, Tokyo Denki University; and Avelino J. Gonzalez, University of Central Florida

The success of Turing Test technologies for system validation depends on the quality of the human expertise behind the system. The authors developed models of collective and individual human expertise, which are shortly outlined here. The focus of the paper is an experimental work aimed at determining the quality of these models. The models have been used for both solving problem cases and rating (other agents') solutions to these cases. By comparing the models’ solutions and ratings with those of the human original we derived assessments of their quality. An analysis revealed both the general usefulness and some particular weaknesses.


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