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Representation and Use of Explicit Justifications for Knowledge Base Refinements

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Proceedings of the Ninth International Joint Conference on Artificial Intelligence. Learning and Acquisition. Pages 673-679.

Abstract

We discuss the representation and use of justification structures as an a id to knowledge base refinement . We s how how justifica· lions can be used by a system to generate explanations- for its o wn use- of potential causes of observed failures. We discuss specific information that is usefully included in these justifications to allow th e system to isolate potential faulty supporting beliefs for its rules and to effect repa1rs . This research is part of a larger effort to develop a Learning Apprentice System (LAS) that partially automates initial construction of a knowledge base from first -principle domain knowledge as well as knowledge base refinement during routine use. A simple implementation has been constructed that demonstrates the feasi bility of building such a system.

Reid G. Smith, Howard A. Winston, Tom M. Mitchell, and Bruce G. Buchanan. 1985. Representation and Use of Explicit Justifications for Knowledge Base Refinements. In Proceedings of the Ninth International Joint Conference on Artificial Intelligence, IJCAI-85. IJCAI, 673–679. https://ijcai.org/proceedings/1985/131
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