{"updated":"2025-01-19T21:29:34.675513+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00199964","sets":["6164:6165:6210:9955"]},"path":["9955"],"owner":"44499","recid":"199964","title":["進化計算法を用いた詰将棋の自動生成"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-11-01"},"_buckets":{"deposit":"a30bb939-4e81-406f-ade5-f19b6466b3d6"},"_deposit":{"id":"199964","pid":{"type":"depid","value":"199964","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"進化計算法を用いた詰将棋の自動生成","author_link":["485468","485471","485469","485470"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"進化計算法を用いた詰将棋の自動生成"},{"subitem_title":"Tsume-Shogi problem composition using evolutionary computation","subitem_title_language":"en"}]},"item_type_id":"18","publish_date":"2019-11-01","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"横浜国立大学院環境情報府"},{"subitem_text_value":"横浜国立大学院 環境情報研究院"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Environment and Information Sciences, Yokohama National University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Environment and Information Sciences, Yokohama National 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/199964/files/IPSJ-GPWS2019001.pdf","label":"IPSJ-GPWS2019001.pdf"},"date":[{"dateType":"Available","dateValue":"2019-11-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-GPWS2019001.pdf","filesize":[{"value":"1.7 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":"18"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"70db3132-8f05-4141-bfca-056b4812097b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"宗藤, 大貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"長尾, 智晴"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Daiki, Muneto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tomoharu, Nagao","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":"人工知能の発展により，様々な論理パズル問題を人間の事前知識なしで解く能力は年々向上している．しかし，パズル問題の創作に関しては，解が一つでないことや生成された問題の評価が難しいことから解答に比べ困難なタスクである．本稿では，パズル問題の中でも，持ち駒があるなどの性質から創作が難しいと考えられる詰将棋を題材とする．エキスパートによる詰将棋創作では，短手数の詰将棋や長手数の余詰めのある詰む局面の情報を利用する．この考え方に基づき，進化計算法の 1 つである遺伝的アルゴリズムによって，局面の変換を最適化することで長手数の詰将棋を生成する手法を提案する．実験の結果，最長で 31 手詰めの詰将棋が生成できることが確認できた． ","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"With the development of artificial intelligence, the ability to solve various logic puzzle problems without human knowledge is improving year by year. However, creating puzzle problems is a more difficult task than answering because there is no single solution and it is difficult to evaluate the created problem. In this paper, we focus on the chess shogi, which is thought to be difficult to create due to the nature of the puzzles problem. The expert uses the information on shorter-move mates or incomplete mates in composition. Based on this idea, we propose a method to compose longer-move mates by optimizing the board conversion by using a genetic algorithm, which is one of the evolutionary computation methods. As a result of the experiment, it was confirmed that 31-move mate can be generated.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"ゲームプログラミングワークショップ2019論文集"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-11-01","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2019"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:03:41.206272+00:00","id":199964,"links":{}}