Learning by Molecular Robot Swarm
| Project/Area Number |
17K19961
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Information science, computer engineering, and related fields
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Hagiya Masami 東京大学, 大学院情報理工学系研究科, 教授 (30156252)
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| Project Period (FY) |
2017-06-30 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Fiscal Year 2019: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2017: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | DNAコンピュータ / 分子ロボット / 群ロボット / 自己組織化 / 機械学習 / ＤＮＡコンピュータ |
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| Outline of Final Research Achievements |
This research is intended to construct a new information processing model that combines high-speed information processing by electronic circuits and low-speed information processing by chemical reactions, and realize swarm intelligence by molecular robots composed of molecular devices. With that as the ultimate goal, a swarm of molecular robots (molecular robot swarm) was modeled as cellular automata (called a gellular automata), and distributed algorithms were constructed to form various patterns such as paths and spanning trees by a swarm of molecular robots. Furthermore, distributed algorithms that synthesize a logic circuit from input-output training data were constructed under cellular automata extended with signal propagation that imitates a chemical gradient and high-speed signal transmission as in an electronic circuit.
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| Academic Significance and Societal Importance of the Research Achievements |
脳においては、アクソンが伸長することによりニューロン間のネットワークが形成されシナプスが変化することにより、長期的な情報処理である学習が行われる。パルスの伝達が一過性であるのに対して、アクソンの伸長やシナプスの変化においては、化学反応の影響が蓄積されネットワークの構造として定着する。このような学習の仕組みを倣って、将来的に人工的に同様の機能を分子で作られたデバイスによって実現するために、主としてセルオートマトンという数理モデルを用いて、ネットワーク形成の仕組みを構成した。
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Report
(5 results)
Research Products
(16 results)
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[Journal Article] Self-stabilizing Gellular Automata2019
Author(s)
Tatsuya Yamashita, Akira Yagawa, Masami Hagiya
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Journal Title
UCNC 2019: Unconventional Computation and Natural Computation, Lecture Notes in Computer Science
Volume: 11493
Pages: 272-285
DOI
ISBN
9783030193102, 9783030193119
Related Report
Peer Reviewed
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