| Budget Amount *help |
¥13,260,000 (Direct Cost: ¥10,200,000、Indirect Cost: ¥3,060,000)
Fiscal Year 2016: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2015: ¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2014: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
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| Outline of Final Research Achievements |
As a result of the recent revival in Evo-Devo (Evolutionary Developmental Biology), dramatic changes are occurring in regard to our understanding of the genetic control networks of organisms. In this direction, there are high expectations for the application of gene regulatory networks (GRNs) to various fields, e.g., robotics, engineering design, architectures, etc., because of their intrinsic robustness and modularity as well as the possibility of evolution and compression of complex expression. We have established the evolutionary framework of GRNs through differential evolution for learning of networks that generate multiple motion, and verifies whether the networks generate motion correctly using simulators and actual robots.
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