| Project/Area Number |
63550273
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計算機工学
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| Research Institution | KYOTO UNIVERSITY |
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Principal Investigator |
NISHIDA Toyoaki Kyoto University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (70135531)
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| Co-Investigator(Kenkyū-buntansha) |
SHIMADA Yoichi Kyoto University, Faculty of Engineering, Assistant Professor, 工学部, 助手 (70196492)
DOSHITA Shuji Kyoto University, Faculty of Engineering, Professor, 工学部, 教授 (00025925)
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| Project Period (FY) |
1988 – 1989
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| Project Status |
Completed (Fiscal Year 1989)
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| Budget Amount *help |
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1989: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1988: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | qualitative reasoning / engineering problem solving / artificial intelligence / commonsense reasoning / dynamical systems / 人口知能 / ヒューリスティック / 量に関する不十分な情報の管理 |
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| Research Abstract |
Qualitative reasoning plays an important role in human problem solving process. Given a complex problem, human experts first try to grasp qualitative nature of the problem by rough analysis. This kind of mental process has received much less attention than quantitative computation.
The purpose of this research is to model and implement qualitative reasoning by human experts and to establish a well founded ground for engineering problem solving.
The result of this research can be summarized as follows: 1. Studies on qualitative representation and reasoning about commonsense Knowledge about space. We have developed a method of reasoning about three-dimensional spatial configuration using a technique called potential model. We developed a potential minimization algorithm applicable to high dimensional parameter space concerning space such as position, size, shape, orientation, or neighborhood. 2. Studies on maintenance and utilization of incomplete information about quantity. We have developed a system which can answer questions by maximally making use of available information. We employed various kind of heuristic knowledge for this system. 3. Automated modeling by heuristic knowledge. We have developed a program which can automatically produce a model appropriate for a given problem by applying various model modification operators to basic model components. We make use of heuristic knowledge concerning causal analysis of underlying differential equations.
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