Automating knowledge acquisition as extending, updating, and improving a knowledge base

G.D. Tecuci
1992 IEEE Transactions on Systems, Man and Cybernetics  
ABS1RACT The paper presents an approach to the automation of knowledge acquisition for expert systems. The approach is based on several general principles emerging from the field of machine learning: expert system building as a three phase process, understanding-based knowledge extension, knowledge acquisition through multistrategy learning, consistency-driven concept formation and refinement, closed-loop learning. and synergistic cooperation between the human expert and the learning system. In
more » ... learning system. In this approach, an expert system is built by a human expert and a learning system. The human expert defmes the framework for the expert system and provides an incomplete and partially incorrect knowledge base. The learning system incrementally extends, updates, and improves the knowledge base through learning from the human expert. This approach is illustrated by the learning system shell NeoDISCIPLE :I< Joint appointment with the Research Institute for Informatics, 71316, Bd.Mrs.Averescu 8-10, Bucharest 1, Romania ,. It should be noticed that the system may be able to prove "(x GROWS-IN y)" by building other justification trees. Considering all the plausible proof tree, however, would not be computational feasible. and would require an unaccep·table long interaction with the human expert.
doi:10.1109/21.199468 fatcat:xqtviwubszbhrkhnied5ee5cje