Toward reducing human involvement in validation of knowledge-based systems

Human experts employed in validation exercises for knowledge-based systems (KBSs) often have limited time and availability. Furthermore, they often have different opinions from each other as well as from themselves over time. We address this situation by introducing the use of validation knowledge used in prior validation exercises for the same KBS. We present a validation knowledge base (VKB) that is the collective best experience of several human experts. The VKB is constructed and maintained across various validation exercises, and its primary benefits are given as follows: 1) more reliable validation results by incorporating external knowledge and 2) decrease of the experts' workload. We also present the concept of validation expert software agents (VESAs), which represent a particular expert's knowledge. VESA is a software agent corresponding to a specific human expert. It models the validation knowledge and behavior of its human counterpart by analyzing similarities with the responses of other experts. After a learning period, it can be used to temporarily substitute for its corresponding human expert. We also describe experiments with a small prototype system to evaluate the usefulness of these concepts.