{"id":175340,"updated":"2025-01-20T06:15:23.344928+00:00","links":{},"created":"2025-01-19T00:45:17.401051+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00175340","sets":["6164:6165:6210:8931"]},"path":["8931"],"owner":"11","recid":"175340","title":["Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-10-28"},"_buckets":{"deposit":"dc61e864-bd98-4525-98f1-9edfa20a5da5"},"_deposit":{"id":"175340","pid":{"type":"depid","value":"175340","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go","author_link":["365044","365045","365050","365049","365046","365051","365048","365047"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go"},{"subitem_title":"Deep Convolutional Neural Network, Minorization-Maximization Algorithm, and Monte Carlo Tree Search on Block Go","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Block Go, Monte Carlo Tree Search, Minorization-maximization algorithm, Deep Convolutional\\nNeural Network, Machine Learning","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2016-10-28","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science and Information Engineering, National Dong Hwa University"},{"subitem_text_value":"Department of Computer Science and Information Engineering, National Dong Hwa University"},{"subitem_text_value":"Department of Computer Science and Information Engineering, National Dong Hwa University"},{"subitem_text_value":"Department of Applied Mathematics, Chung Yuan Christian University"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science and Information Engineering, National Dong Hwa University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science and Information Engineering, National Dong Hwa University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science and Information Engineering, National Dong Hwa University","subitem_text_language":"en"},{"subitem_text_value":"Department of Applied Mathematics, Chung Yuan Christian University","subitem_text_language":"en"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/175340/files/IPSJ-GPWS2016011.pdf","label":"IPSJ-GPWS2016011.pdf"},"date":[{"dateType":"Available","dateValue":"2016-10-28"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-GPWS2016011.pdf","filesize":[{"value":"872.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"18"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a7342c4f-4939-403f-8ba8-478f7e6aba31","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shi-Jim, Yen"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keng, Wen Li"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Chingnung, Lin"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jr-Chang, Chen"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shi-Jim, Yen","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keng, Wen Li","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Chingnung, Lin","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jr-Chang, Chen","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"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.","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"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.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"72","bibliographic_titles":[{"bibliographic_title":"ゲームプログラミングワークショップ2016論文集"}],"bibliographicPageStart":"69","bibliographicIssueDates":{"bibliographicIssueDate":"2016-10-28","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2016"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}