CLASSIC: a structural data model for objects
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Logic-based configuration with a semantic network
Journal of Logic Programming - Logic programming applications
A formal theory of plan recognition and its implementation
Reasoning about plans
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
IAAI '93 Proceedings of the The Fifth Conference on Innovative Applications of Artificial Intelligence
Configuration as a Consistency Maintenance Task
Künstliche Intelligenz, GWAI-88, 12. Jahrestagung
Closed terminologies and temporal reasoning in description logic for concept and plan recognition
Closed terminologies and temporal reasoning in description logic for concept and plan recognition
The description logic handbook
Decomposition strategies for configuration problems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
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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.