Knowledge Structural Modeling for Developing Expert Systems.

知识获取是开发专家系统的瓶颈。本研究旨在利用柔性解释结构建模（FISM），开发一种新的有效的知识获取方法。该研究项目计划为期两年，从1990年至1991年。第一阶段的主要研究结果如下：1.研究结果表明：对多种知识获取方法进行了调查。重点讨论了个人构形理论在知识获取系统ETS中的应用。考虑了FISM函数的扩展，以处理多维关系和关联度。第二阶段的结果总结如下：1。为了考虑关联度，引入了模糊二元关系。通过引入互连关系矩阵来处理多维关系。测试系统在AS4330工作站上实现。结果应用于计算机语言的自动推理、定量推理和语法学习。此后如何处理基于案例的推理问题仍然存在。

Knowledge acquisition is the bottle neck of developing experts systems. This research project aimed to develop a new effective method for knowledge acquisition by applying Flexible Interpretive Structural Modeling (FISM) Which is a method used to construct systems structural modeling. The research project was planed for a period of two years, from 1990 to 1991. The main results of the first period are as follows :1. Many knowledge acquisition methods were surveyed. Especially, Personal construct theory which is used in a knowledge acquisition system ETS was discussed,2. Extension of functions of FISM to treat multidimensional relation and degrees of relation were considered.The results of the second period are summarized as fololws :1. Fuzzy binary relation was introduced for considering the degree of relation,2. Multidimensional relation was treated by introducing the interconnection relation matrix,3. A test system was implemented on an AS4330 work station,4. Results were applied to automated reasoning, quantitative reasoning and syntax learning of computer languages.The problem of how to deal with the case based reasoning hereafter still remains.