| Project/Area Number |
11480079
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Saitama University |
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Principal Investigator |
CHENG Jingde Saitama University, Graduate School of Science & Engineering, Professor, 大学院・理工学研究科, 教授 (30217228)
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| Co-Investigator(Kenkyū-buntansha) |
NOMURA Yoshinari Kyushu University, Graduate School of Information Science & Electrical Engineering, Research Associate, 大学院・システム情報科学研究院, 助手 (70274496)
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| Project Period (FY) |
1999 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥5,900,000 (Direct Cost: ¥5,900,000)
Fiscal Year 2002: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2001: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 1999: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Keywords | scientific discovery / epistemic processes / epistemic programming / strong relevant logic / relevant reasoning / ampliative reasoning / autonomous evolution / automated theorem finding / 自己計測 |
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| Research Abstract |
1. We proposed some significant fundamental observations and assumptions on scientific discovery processes and their automation. Based on the observations and assumptions, we proposed a strong relevant logic model of epistemic processes in scientific discovery.
2. Based on our strong relevant logic model of epistemic processes in scientific discovery, we proposed a novel program paradigm, named 'Epistemic Programming,' which regards conditionals as the subject of computing, takes primary epistemic operations as basic operations of computing, and regards epistemic processes as the subject of programming.
3. We pointed out why the classical mathematical logic and its various classical and non-classical conservative extensions are not suitable to automated theorem finding, and shows that strong relevant logic is a more hopeful candidate for the purpose.
4. We developed a forward deduction system for general-purpose entailment calculus, named EnCal, which can serve as the forward reasoning engine in an epistemic programming system. We improved the efficiency of EnCal by parallel processing techniques.
5. We proposed the notion of autonomous evolutionary information system and its architecture.
6. We proposed the notion of anticipatory reasoning-reacting system and showed that temporal relevant logics, which are obtained by introducing temporal operators and related axiom schemata and inference rules into strong relevant logics, can be used to underlie anticipatory reasoning.
7. We proposed a new approach to knowledge acquisition problem : automated knowledge acquisition by relevant reasoning based on strong relevant logic.
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