| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Outline of Final Research Achievements |
The purpose of this study is to develop a new genetic programming for large tree optimization in order to solve the design problem consisting of variables expressed in tree structure such as expressions and program generation for autonomous control. The achieved works of this study are: (1) Improvement of a multi step crossover that has high trait integrity, (2) Development of an initialization scheme based on preferable trait estimation by past search information, and (3) Development of a search scheme for obtaining new traits. We showed the effectiveness and application guidelines of the proposed method mainly through the performance analysis using the function regression problem.
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