PROBLEMS OF DECISION RULE ELICITATION IN A CLASSIFICATION TASK

Intelligent decision support requires knowledge elicitation processes. Two primary approaches for knowledge elicitation in a multiattribute classification task are 1) direct elicitation of decision rules in the form of productions, and 2) classification of multiattribute objects by an expert as a basis for development of the underlying decision rul es. This study reports an experiment using a simple classification tas k, to compare these two forms of knowledge elicitation. Relative consi stency and complexity of the resulting rule bases are analyzed. System CLASS was used as a tool for the second approach, as well as a means of analysis for the first approach. It was found that it was easier fo r subjects to accomplish the task using object classification than it was to formulate production rules directly. High degrees of inconsiste ncy and incomplete rule bases resulted when there was no computer aid for the process of knowledge elicitation.