Multi-objective stochastic search based on network topology and its application to evolutionary robotics
| Project/Area Number |
22500201
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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 | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2010: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 粒子群最適化 / 多目的最適化 / 進化計算 / RoboCup Soccer Simulation / Particle Swarm Optimization / RoboCupサッカーシミュレーション3D / ネットワーク構造 / 二足歩行ロボット / CMA-ES |
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| Research Abstract |
To obtain Pareto optimal set is primary important for the multi-objective optimization that consists of plural objective functions. From this point of view, multipoint search methodology has attracted attention, since it is able to provide the Pareto optimal candidates by single run. In this study, we have considered stochastic multi-point search methodology for multi-objective optimization based on the search point network to define the information sharing range among search points. In addition, we discussed an application to motion acquisition of the soccer robot in the RoboCup soccer simulation.
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Report
(4 results)
Research Products
(33 results)
