Presentation | 2014-01-21 An approach to develop the game agent based on Self-Organizing Map and Reinforcement learning Keiji Kamei, Yuuki KAKIZOE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, there have been many board game agents such as Chess and Shogi, and they could occasionally defeat professionals. The agents are able to predict possible variations of moves and their efficiencies depend on the improvement in performance of computers. At the moment our purpose is to make a game agent which has low processing ability like human beings. In this paper, we propose to apply SOM and RL for developing the game agent which plays Othello game. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Game Agent / Othello / Reversi / Reinforcement Learning / Self-Organizing Map(SOM) |
Paper # | NC2013-80 |
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Committee | NC |
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Conference Date | 2014/1/13(1days) |
Place (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) | An approach to develop the game agent based on Self-Organizing Map and Reinforcement learning |
Sub Title (in English) | |
Keyword(1) | Game Agent |
Keyword(2) | Othello |
Keyword(3) | Reversi |
Keyword(4) | Reinforcement Learning |
Keyword(5) | Self-Organizing Map(SOM) |
1st Author's Name | Keiji Kamei |
1st Author's Affiliation | Graduate School of Engineering, Nishinippon Institute of Technology() |
2nd Author's Name | Yuuki KAKIZOE |
2nd Author's Affiliation | Graduate School of Engineering, Nishinippon Institute of Technology |
Date | 2014-01-21 |
Paper # | NC2013-80 |
Volume (vol) | vol.113 |
Number (no) | 382 |
Page | pp.pp.- |
#Pages | 6 |
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