| Project/Area Number |
16500135
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | University of Hyogo |
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Principal Investigator |
MATSUI Nobuyuki University of Hyogo, Graduate School of Engineering, Professor, 大学院工学研究科, 教授 (10173783)
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| Co-Investigator(Kenkyū-buntansha) |
ISOKAWA Teijiro University of Hyogo, Graduate School of Engineering, Associate Professor, 大学院工学研究科, 准教授 (70336832)
NISHIMURA Haruhiko University of Hyogo, Graduate School of Applied Informatics, Professor, 大学院応用情報科学研究科, 教授 (40218201)
PEPER Ferdinand National Institute of Information and Communications Technology, Kansai Advanced Research Center, Senior Researcher, 関西先端研究センター, 主任研究員 (40359097)
KAMIURA Naotake University of Hyogo, Graduate School of Engineering, Associate Professor, 大学院工学研究科, 准教授 (80275312)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2006: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2005: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2004: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | neural network / SOM / cellular automaton / quaternion / qubit / reinforcement learning / image processing / data mining / 結合問題 / 非標準計算論 / 潜在的機能発現 / 創造的情報処理 / カオス |
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| Research Abstract |
In this research, we tried to find the methods of creative thinking based on non-standard computation toward brain potentiality such as perceptual alternation phenomena and investigated the emergence of this creative effect through system applications to these methods. In our study of the creative information processing systems, we have obtained the following main results:
1. We found the multiplet as the characteristics of association in discrete states and discrete time Hopfield neural network described by quaternion.
2. We confirmed the efficiency of the qubit neural network in the color night vision and data-mining applications.
3. We developed the block learning SOM system with high adaptability under non-stationary environments.
4. We cleared the efficiency of the multi-stable perception model by multi-layered bi-directional associative memory.
5. We derived flocking behaviors of agents from a scheme of reinforcement learning, and also clarified the effect of reinforcement learning using chaotic exploration in the maze world problem.
6. We constructed the algorithms on defect-tolerance in the asynchronous cellular automaton and showed that defective cells are detected and isolated by configurations of random flies that move around in cellular space.
As a result, we clarified that our creative information processing systems have better performances than conventional ones in processing various problems. We have presented a lot of our fruitful results so that we consider our research aims have been achieved. However, many subjects remain to be explored, for examples, Clifford algebra approach, Bloch representation on qubit neuron state and its application to cellular neural network, etc. These are our future works.
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