Presentation | 2003/1/28 Multi-agent Reinforcement Learning on Collective Decision-Making : Designing E-Democracy Hiroshi YAMAKAWA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In recent years, E-Democracy became realistic. In E-Democracy, a flexible system design is possible compared with the conventional democracy. Thereby, the better system which reflects public opinion appropriately may be able to be designed. However, in the present state, the system design technique of collective decision-making is not established. Multi-agent reinforcement learning is one powerful approach carried out to such a design subject. In this report, first, I explain a possibility by new design of E-Democracy system. Second, I present the simple simulation of MA-RL. Third, I compare the subject of collective decision-making and the subject of MA-RL. By the above-mentioned argument, the potentiality of MA-RL as system design technology of collective decision-making was explored. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Direct Democracy / Reinforcement Learning / Collective Decision-Making / Multi-agent System |
Paper # | NC2002-124 |
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Committee | NC |
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Conference Date | 2003/1/28(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Multi-agent Reinforcement Learning on Collective Decision-Making : Designing E-Democracy |
Sub Title (in English) | |
Keyword(1) | Direct Democracy |
Keyword(2) | Reinforcement Learning |
Keyword(3) | Collective Decision-Making |
Keyword(4) | Multi-agent System |
1st Author's Name | Hiroshi YAMAKAWA |
1st Author's Affiliation | Grid Computing & Bioinfomatics Lab. FUJITSU LABORATORIES LTD.() |
Date | 2003/1/28 |
Paper # | NC2002-124 |
Volume (vol) | vol.102 |
Number (no) | 628 |
Page | pp.pp.- |
#Pages | 6 |
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