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

基于深度知识的具有知识编译功能的专家系统工具开发

基本信息

批准号：
03452290
负责人：
MIZOGUCHI Riichiro
金额：
$ 0.45万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1991
资助国家：
日本
起止时间：
1991 至 1992
项目状态：
已结题

项目摘要

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.

本研究的主要目的是开发创新的知识处理技术，有助于克服现有技术的局限性，如脆性和缺乏适应性。人类专家拥有基础知识和领域原则（深层知识），以及用于解决普通问题的知识（浅层知识）。当他们遇到不熟悉的问题时，他们不能用数学来解决，他们试图用上面提到的深层知识来解决。基于此，研究者开展了基于深层知识的专家系统和浅层知识的知识编译研究。本文的主要成果之一是建立了一个基于五种深层知识的诊断专家系统知识编译系统。基于模型的推理是对定性建模动态系统行为环境的研究，它与基于模型的推理有着密切的联系。定性推理的缺点之一是推理的模糊性，这使得定性推理方法不能应用于实际问题。本研究的另一个目的是开发一种新的定性推理方法，以减少歧义。设计了核动力装置冷却子系统的建模方法和推理方法。本研究的第三个目标是开发一种可重用知识库的构建方法。虽然尚未完成，第一个版本的方法已经设计的知识库恢复变电站。