| Project/Area Number |
01460253
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Informatics
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| Research Institution | Hokkaido University |
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Principal Investigator |
OHUCHI Azuma Hokkaido University, Fac. of Engineering, Professor, 工学部, 教授 (50002308)
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| Co-Investigator(Kenkyū-buntansha) |
ENDOU Satoshi Hokkaido University, Fac. of Engineering, Instructor, 工学部, 助手 (00223686)
OHYANAGI Toshio Hokkaido Univesity, Fac. of Engineering, Instructor, 工学部, 助手 (70177020)
KURIFARA Masahito Hokkaido University, Fac. of Engineering, Assistant Professor, 工学部, 助教授 (50133707)
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| Project Period (FY) |
1989 – 1990
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| Project Status |
Completed (Fiscal Year 1990)
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| Budget Amount *help |
¥6,600,000 (Direct Cost: ¥6,600,000)
Fiscal Year 1990: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1989: ¥5,600,000 (Direct Cost: ¥5,600,000)
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| Keywords | Expert System / Knowledge Acquisition / Structural Modeling / E T S / Fuzzy / Personal Construct Grid Method / ファジィ / 人工知能 / 二項関係 |
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| Research Abstract |
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.
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