Constructing and Refining Ontologies within Explanation-Capable Agents

In this paper a technique that enables the dialogbased construction and refinement of operationalized ontologies is proposed. An agent learns classification knowledge through a dialog with a teacher. In this dialog the agent is forced to provide logical explanations of why it classifies (or fails to classify) an instance to various ontology concepts. The teacher is able to give immediate and very focused feedback through these dialogs. This enables the agent to be taught classification knowledge through the treatment of only a handful of examples. And the teacher’s feedback is through conversational point, click, and field-filling interactions. What differentiates this approach is that this work leverages off of, and builds on previous work in which a complete system of concept equations may be solved over a practical subset of relational schemas. The ability to syntactically compute query difference enables the calculation of concept intersections and differences, and the determination of concept subsumption and disjointness. The knowledge repair algorithms outlined in this paper require this capability.