{"updated":"2025-01-19T23:15:56.132078+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00194974","sets":["1164:5305:9738:9739"]},"path":["9739"],"owner":"44499","recid":"194974","title":["少ない棋譜からの将棋プレイヤ棋力推定手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-03-01"},"_buckets":{"deposit":"6e5a7176-c24b-4281-8259-1b28148c9b67"},"_deposit":{"id":"194974","pid":{"type":"depid","value":"194974","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"少ない棋譜からの将棋プレイヤ棋力推定手法の提案","author_link":["463037","463036","463038","463035"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"少ない棋譜からの将棋プレイヤ棋力推定手法の提案"},{"subitem_title":"Shogi Player's Rating Estimation Method using Fewer Game Records","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2019-03-01","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"電気通信大学"},{"subitem_text_value":"電気通信大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The University of Electro-Communications","subitem_text_language":"en"},{"subitem_text_value":"The University of Electro-Communications","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/194974/files/IPSJ-GI19041013.pdf","label":"IPSJ-GI19041013.pdf"},"date":[{"dateType":"Available","dateValue":"2021-03-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-GI19041013.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"18"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"888c7598-30f7-476b-b13a-5c7fd633e060","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"馬場, 匠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"伊藤, 毅志"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takumi, Baba","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Ito","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11362144","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8736","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本研究では，なるべく少ない棋譜から将棋プレイヤの棋力を推定する手法を提案する．先行研究の将棋AIを用いた棋力推定の手法では20局程度の対戦を必要としていた．これは，分析対象とする局面の条件に「序盤や終盤の除外」などの制約があるため，1局あたりの分析局面数が少なることが原因である．本研究では，どのような局面が棋力推定に有効に働くのかを詳細に調べた．その結果，接戦の局面ほど棋力推定に適していることが判明した．そこで，接待将棋AIを用いて接戦の局面を多く作ることにより，少ない対局数から棋力推定をする手法を提案した．この手法により，3～4局程度の対戦でかなり正確に棋力推定ができることを確認した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this research, we propose a method to estimate Shogi players' rating from fewer game records. In the related study of estimating players' rating using Shogi AI, about 20 game records were required. This is due to the fact that there are constraints such as \"exclusion of opening game and end game\" in the condition of the positions to be analyzed, so that the number of analysis positions per a game is very small. In this research, we investigated in detail what kind of position works effectively for rating estimation. As the result, we found that positions in close game are more suitable for rating estimation. Therefore, we proposed a method to estimate players' rating from a small number of games by creating many close game positions using an entertainment shogi AI. By using this method, we confirmed that we can estimate players' rating fairly accurately with 3 or 4 games.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ゲーム情報学（GI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"13","bibliographicVolumeNumber":"2019-GI-41"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T00:59:59.692310+00:00","id":194974,"links":{}}