Development of expert system tools with knowledge compilation function based on deep knowledge

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The major objective of this research is to develop innovative knowledge processing techniques which contribute to overcoming the limitation of the current technology such as brittleness and lack of adaptability. Human experts have fundamental knowledge and domain principles(deep knowledge) in addition to heuristics(shallow knowledge) which is used in solving ordinary problems. When they are given unfamiliar problems they cannot solve by using heuristics, they try to solve it by using above mentioned deep knowledge. Based on this observation, the investigator conducted the research on deep knowledge-based expert system and knowledge compilation of shallow knowledge. One of the main results obtained is a knowledge compilation system based on five kinds of deep knowledge for diagnostic expert systems. A prototype systems has been successfully implemented in Common ESP on Sparkstation.This research has a tight relation to model-based reasoning which is a research on environment of the behavior of qualitatively modeled dynamic systems. One of the shortcomings of the qualitative reasoning is ambiguity of the inference which prevents the method to be used in practical problems. Another objective of this research is to develop a new qualitative reasoning method for decreasing the ambiguity. A modeling method and inference method have been designed for cooling subsystem of a nuclear power plant.The third objective of this research is to develop a methodology for building reusable knowledge base. Although not completed yet, a first version of the methodology has been designed for the knowledge base for restoration of substations.