対象モデルによるハイブリッド型故障診断システム : モデル表現と推論
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概要
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Most currently available knowledge-based expert systems based on a surface knowledge, such as a production rules, can work only for the specific problem solving for a specific problem in a narrow domain. This is because that one rule allows single interpretation and then a complex problem needs a lot of rules according to a variety of situations. For this reason it is difficult to achieve flexible and powerful system by this kind of knowledge. While, a human expert who has the deep knowledge according to the domain can solve variety of problems in the domain using the knowledge. By deep knowledge we mean the knowledge about the principle and the structure on an object. For example, a human expert who knows the principle and the structure of a computer system can express what the computer is to another person, can understand a picture about the computer,can find some failures in the computer design specification, and can make some troubleshootings on the computer. We believe that features to manipulate the deep knowledge might become key technology for next generation expert systems. We have proposed the concept and the modelling method based on the object model as a candidate of deep knowledge system. We developed a trouble-shooting expert system as an application of the object model. The object model can be represented in a extend frame-based knowledge representation formalism by means of a combination of ISA and PART-OF relation, and is represented by combining knowledge about structures and behaviors, and is one of deep knowledge for representing complex structured objects. The behavioral knowledge is represented the relationship between input and output states. We called that behavior rules. The model-based reasoning method using the behavioral knowledge is achieved by evaluation of behavior rules. This paper shows the object modelling and the model-based reasoning based on the object model. The system have demonstrated the troubleshooting of a focal plane shutter. The system was developed using the frame-based knowledge engineering environment ZERO on the AI work station ELIS.
- 1990-09-01
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