Closed Terminologies in Description Logics

No. 1: Agents, AI in Art and Entertainment, Knowledge Representation, and Learning

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 13

Knowledge Representation Belief & Belief Revision

We introduce a predictive concept recognition methodology for description logics based on a new closed terminology assumption. During knowledge engineering, our system adopts the standard open terminology assumption as it automatically classifies concept descriptions into a taxonomy via subsumption inferences. However, for applications like configuration, the terminology becomes fixed during problem solving. Then, closed terminology reasoning is more appropriate. In our interactive configuration application, a user incrementally specifies an individual computer system in collaboration with a configuration engine. Choices can be made in any order and at any level of abstraction. We distinguish between abstract and concrete concepts to formally define when an individual’s description may be considered finished. We also take advantage of the closed terminology assumption, together with the terminology’s subsumption-based organization, to efficiently track the types of systems and components consistent with current choices, infer additional constraints on current choices, and appropriately guide future choices. Thus, we can help focus the efforts of both user and configuration engine.