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アイテム

  1. シンポジウム
  2. シンポジウムシリーズ
  3. ゲームプログラミングワークショップ(GPWS)
  4. 2016

Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go

https://ipsj.ixsq.nii.ac.jp/records/175340
https://ipsj.ixsq.nii.ac.jp/records/175340
38ebd953-a2e3-4c3a-b215-fcad9f5d7f8a
名前 / ファイル ライセンス アクション
IPSJ-GPWS2016011.pdf IPSJ-GPWS2016011.pdf (872.2 kB)
Copyright (c) 2016 by the Information Processing Society of Japan
オープンアクセス
Item type Symposium(1)
公開日 2016-10-28
タイトル
タイトル Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go
タイトル
言語 en
タイトル Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go
言語
言語 eng
キーワード
主題Scheme Other
主題 Block Go, Monte Carlo Tree Search, Minorization-maximization algorithm, Deep Convolutional\nNeural Network, Machine Learning
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_5794
資源タイプ conference paper
著者所属
Department of Computer Science and Information Engineering, National Dong Hwa University
著者所属
Department of Computer Science and Information Engineering, National Dong Hwa University
著者所属
Department of Computer Science and Information Engineering, National Dong Hwa University
著者所属
Department of Applied Mathematics, Chung Yuan Christian University
著者所属(英)
en
Department of Computer Science and Information Engineering, National Dong Hwa University
著者所属(英)
en
Department of Computer Science and Information Engineering, National Dong Hwa University
著者所属(英)
en
Department of Computer Science and Information Engineering, National Dong Hwa University
著者所属(英)
en
Department of Applied Mathematics, Chung Yuan Christian University
著者名 Shi-Jim, Yen

× Shi-Jim, Yen

Shi-Jim, Yen

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Keng, Wen Li

× Keng, Wen Li

Keng, Wen Li

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Chingnung, Lin

× Chingnung, Lin

Chingnung, Lin

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Jr-Chang, Chen

× Jr-Chang, Chen

Jr-Chang, Chen

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著者名(英) Shi-Jim, Yen

× Shi-Jim, Yen

en Shi-Jim, Yen

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Keng, Wen Li

× Keng, Wen Li

en Keng, Wen Li

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Chingnung, Lin

× Chingnung, Lin

en Chingnung, Lin

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Jr-Chang, Chen

× Jr-Chang, Chen

en Jr-Chang, Chen

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論文抄録
内容記述タイプ Other
内容記述 Block Go is similar to the game of Go. The game is introduced by Pro Zhang Xu at 2009. His purpose is to reduce the complexity of Go and let the game be suitable for children. The complexity of Block Go is around 10^45, which is between checker and Othello. In this paper, we will state the rule Go and analyses the complexity of Block. Then, the Block Go program is implemented with Monte Carlo Tree Search (MCTS), and minorization-maximization pattern database. We also apply Deep Convolutional Neural Network (DCNN) on Block Go. In the future, we will apply transfer learning to improve the DCNN of Block Go, based on the numerous Go game records.
論文抄録(英)
内容記述タイプ Other
内容記述 Block Go is similar to the game of Go. The game is introduced by Pro Zhang Xu at 2009. His purpose is to reduce the complexity of Go and let the game be suitable for children. The complexity of Block Go is around 10^45, which is between checker and Othello. In this paper, we will state the rule Go and analyses the complexity of Block. Then, the Block Go program is implemented with Monte Carlo Tree Search (MCTS), and minorization-maximization pattern database. We also apply Deep Convolutional Neural Network (DCNN) on Block Go. In the future, we will apply transfer learning to improve the DCNN of Block Go, based on the numerous Go game records.
書誌情報 ゲームプログラミングワークショップ2016論文集

巻 2016, p. 69-72, 発行日 2016-10-28
出版者
言語 ja
出版者 情報処理学会
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