A Development of Efficient and Large-scale Resource Allocation Method based on 'Yuzuriai' and Votings via the Web
| Project/Area Number |
22700142
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Shizuoka University |
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Principal Investigator |
FUKUTA Naoki 静岡大学, 情報学研究科, 講師 (30345805)
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| Project Period (FY) |
2010-04-01 – 2014-03-31
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 知的エージェント / オークション / エージェント / 人工知能 / 組合せオークション |
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| Research Abstract |
In this research, I focused my effort on extending a market mechanism called "combinatorial auction", and realized an ultra-fast combinatorial auction engine that is also capable to handle massive amount of bids in an auction. Furthermore, I extended my formerly-presented very fast winner determination approximation algorithm to capture a more general problem, called "multi-unit combinatorial auction", and presented prototype algorithms and their evaluations. Also I extended their performance and usability to be applied to a real deployment environment, by applying a good resource allocation mechanism and several fast calculation techniques to be used on a cloud-computing infrastructure.
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Report
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Research Products
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