{"created":"2025-01-19T01:11:52.791011+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210674","sets":["581:10433:10437"]},"path":["10437"],"owner":"44499","recid":"210674","title":["Visualizing and Understanding Policy Networks of Computer Go"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-04-15"},"_buckets":{"deposit":"a04c3cae-3327-4879-a5c7-33cf85c9acd8"},"_deposit":{"id":"210674","pid":{"type":"depid","value":"210674","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Visualizing and Understanding Policy Networks of Computer Go","author_link":["533970","533969","533968","533967"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Visualizing and Understanding Policy Networks of Computer Go"},{"subitem_title":"Visualizing and Understanding Policy Networks of Computer Go","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[一般論文] computer Go, deep learning, visualization, policy network, grad-CAM","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2021-04-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"The University of Electro-Communication"},{"subitem_text_value":"The University of Electro-Communication"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The University of Electro-Communication","subitem_text_language":"en"},{"subitem_text_value":"The University of Electro-Communication","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/210674/files/IPSJ-JNL6204022.pdf","label":"IPSJ-JNL6204022.pdf"},"date":[{"dateType":"Available","dateValue":"2023-04-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL6204022.pdf","filesize":[{"value":"5.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"15d2b309-95ff-411c-b545-4616d0dd861c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuanfeng, Pang"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Ito"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuanfeng, Pang","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Ito","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Deep learning for the game of Go achieved considerable success with the victory of AlphaGo against Ke Jie in May 2017. Thus far, there is no clear understanding of why deep learning performs so well in the game of Go. In this paper, we introduce visualization techniques used in image recognition that provide insights into the function of intermediate layers and the operation of the Go policy network. When used as a diagnostic tool, these visualizations enable us to understand what occurs during the training process of policy networks. Further, we introduce a visualization technique that performs a sensitivity analysis of the classifier output by occluding portions of the input Go board, and revealing parts that important for predicting the next move. Further, we attempt to identify important areas through Grad-CAM and combine it with the Go board to provide explanations for next move decisions.\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.29(2021) (online)\nDOI　http://dx.doi.org/10.2197/ipsjjip.29.347\n------------------------------","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Deep learning for the game of Go achieved considerable success with the victory of AlphaGo against Ke Jie in May 2017. Thus far, there is no clear understanding of why deep learning performs so well in the game of Go. In this paper, we introduce visualization techniques used in image recognition that provide insights into the function of intermediate layers and the operation of the Go policy network. When used as a diagnostic tool, these visualizations enable us to understand what occurs during the training process of policy networks. Further, we introduce a visualization technique that performs a sensitivity analysis of the classifier output by occluding portions of the input Go board, and revealing parts that important for predicting the next move. Further, we attempt to identify important areas through Grad-CAM and combine it with the Go board to provide explanations for next move decisions.\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.29(2021) (online)\nDOI　http://dx.doi.org/10.2197/ipsjjip.29.347\n------------------------------","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2021-04-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"62"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":210674,"updated":"2025-01-19T18:03:38.298712+00:00","links":{}}