{"id":231842,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231842","sets":["581:11492:11493"]},"path":["11493"],"owner":"44499","recid":"231842","title":["少数サンプルから多様なゲームステージを生成するGANの学習手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-01-15"},"_buckets":{"deposit":"05ecec60-a4ec-4610-bf03-574d4009e963"},"_deposit":{"id":"231842","pid":{"type":"depid","value":"231842","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"少数サンプルから多様なゲームステージを生成するGANの学習手法の提案","author_link":["626917","626915","626918","626912","626916","626913","626919","626914"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"少数サンプルから多様なゲームステージを生成するGANの学習手法の提案"},{"subitem_title":"Diverse Level Generation for Tile-based Video Game Using Generative Adversarial Networks from Few Samples","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[特集:エージェント理論・技術とその応用] Procedural Content Generation, Tile-based Level Generation, Generative Adversarial Networks, Deep Learning","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2024-01-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報学専攻"},{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報学専攻"},{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報学専攻"},{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報学専攻"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"University of Electro-Communications Graduate School of Informatics and Engineering Department of Informatics","subitem_text_language":"en"},{"subitem_text_value":"University of Electro-Communications Graduate School of Informatics and Engineering Department of Informatics","subitem_text_language":"en"},{"subitem_text_value":"University of Electro-Communications Graduate School of Informatics and Engineering Department of Informatics","subitem_text_language":"en"},{"subitem_text_value":"University of Electro-Communications Graduate School of Informatics and Engineering Department of Informatics","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/231842/files/IPSJ-JNL6501010.pdf","label":"IPSJ-JNL6501010.pdf"},"date":[{"dateType":"Available","dateValue":"2026-01-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL6501010.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":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"f623f859-88f3-483d-9e15-08e2c9ee5f7c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"高田, 宗一郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"清, 雄一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田原, 康之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大須賀, 昭彦"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Soichiro, Takata","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yuichi, Sei","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuyuki, Tahara","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Akihiko, Ohsuga","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_publisher_15":{"attribute_name":"公開者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"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":"ビデオゲームにおけるステージの生成は，ゲームの楽しさの向上や制作コストの軽減を目的として長年自動生成の研究が行われており，近年では深層学習を用いた手法が研究されるようになってきている．深層学習によるステージ生成では，タイルベースのビデオゲームにおいてGANによる手法が成果をあげているが，その学習データの用意は課題である．そこで，本研究では少数のサンプルのみからGANを学習し，多様なステージを生成可能なモデルを獲得する手法を提案する．本研究では，GANによるステージ生成の先行研究で用いられていた手法を改善した手法およびGANの学習時の損失関数に多様性を向上させる正則化項を加えて学習を行う手法を提案する．3つのタイルベースの2Dゲーム環境において，提案する手法により生成したステージ群に対し，その多様性を評価する評価指標を用意し，それにより定量的な評価を行った．その結果，従来手法によるモデルよりも制約を満たすステージの生成率は低下したものの，多様なステージが生成できることが確認できた．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Automatic level generation for video games has been studied for many years in order to improve game enjoyment and reduce production costs. Although GAN-based methods have been successful in deep learning level generation for tile-based video games, the preparation of training data is a issue. In this study, we propose a method for learning GANs from a small number of samples to obtain a model that can generate a variety of levels. We propose a method that improves on the method used in previous studies of level generation using GANs, and a method that adds a regularization term to the loss function during GAN training to improve diversity. We evaluated the diversity of the levels generated by the proposed method in 3 tile-based 2D game environments using a quantitative evaluation metric. The results showed that the proposed method was able to generate more diverse levels than the existing method, although the rate of levels satisfying the constraints was lower than that of the existing model.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"82","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"69","bibliographicIssueDates":{"bibliographicIssueDate":"2024-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"65"}]},"relation_version_is_last":true,"item_2_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.20729/00231732","subitem_identifier_reg_type":"JaLC"}]},"weko_creator_id":"44499"},"updated":"2025-01-19T10:36:17.136691+00:00","created":"2025-01-19T01:32:22.809618+00:00","links":{}}