Automated Generation of Heuristics Using Genetic Programming
Project/Area Number |
20700131
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Single-year Grants |
Research Field |
Intelligent informatics
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Research Institution | Tokyo Institute of Technology |
Principal Investigator |
福永 Alex (福永 ALEX) Tokyo Institute of Technology, 大学院・総合文化研究科, 准教授 (90452002)
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Project Period (FY) |
2008 – 2010
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Project Status |
Completed (Fiscal Year 2010)
|
Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2008: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
|
Keywords | 人工知能 / 進化計算 / 探索 |
Research Abstract |
Developing effective algorithms for constraint satisfaction and optimization, including task allocation and automated planning in robots and autonomous agents, is a difficult problem. We investigated the use of genetic programming for automatically generating heuristics to solve difficult optimization and constraint satisfaction problems. Using a parallel genetic programming system on a large-scale parallel cluster, we generated new, effective heuristics for SAT. We also used genetic programming to generate action selection heuristics for a museum guide robot. In addition, we also developed new exact and heuristic methods for the multiple knapsack problem.
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Report
(4 results)
Research Products
(30 results)
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[Presentation] ロバストな分散GA2010
Author(s)
Gong Yiyuan, 福永Alex
Organizer
人工知能学会第5回進化計算フロンティア研究会
Place of Presentation
東京工業大学(大岡山キャンパス)
Year and Date
2010-06-04
Related Report
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