{"id":240722,"updated":"2025-01-19T07:53:21.578013+00:00","links":{},"created":"2025-01-19T01:45:04.235216+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240722","sets":["6164:6165:6210:11853"]},"path":["11853"],"owner":"44499","recid":"240722","title":["タワーディフェンスゲームにおけるタワー配置探索の導入"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-11-15"},"_buckets":{"deposit":"d62baa44-d19f-4b4d-bdd6-e2c0ba51cb29"},"_deposit":{"id":"240722","pid":{"type":"depid","value":"240722","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"タワーディフェンスゲームにおけるタワー配置探索の導入","author_link":["660892","660895","660894","660893"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"タワーディフェンスゲームにおけるタワー配置探索の導入"},{"subitem_title":"Incorporating Optimal Tower Placement Search into Player AI for Tower Defense Games","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"プレイヤーAI","subitem_subject_scheme":"Other"},{"subitem_subject":"タワーディフェンスゲーム","subitem_subject_scheme":"Other"},{"subitem_subject":"評価関数","subitem_subject_scheme":"Other"},{"subitem_subject":"探索","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2024-11-15","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":"明治大学大学院先端数理科学研究科"},{"subitem_text_value":"明治大学大学院先端数理科学研究科"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Meiji univ.","subitem_text_language":"en"},{"subitem_text_value":"Meiji univ.","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/240722/files/IPSJ-GPWS2024004.pdf","label":"IPSJ-GPWS2024004.pdf"},"date":[{"dateType":"Available","dateValue":"2024-11-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-GPWS2024004.pdf","filesize":[{"value":"950.6 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":"ea187d55-bb55-49f5-98f7-39ef107534d5","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"野村, 大輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"秋岡, 明香"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Daisuke, Nomura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Sayaka, Akioka","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":"タワーディフェンスゲーム（TD） で開発された AI は実世界上の様々な問題に応用が可能である．そこで，これまで TD でタワーの配置を最適化するプレイヤーAI の開発を行ってきた． しかし， 開発したプレイヤーAI が学習したマップしか攻略できないという問題が存在する． そこで，本研究では新しいアプローチとして， TD のプレイヤーAI に評価関数と探索を導入する．評価関数は，ウェーブが攻略できるかを判断する ． 結果， 評価関数はタワーの少ない盤面では有効性が確認されたが，タワーの数が増加した場合の評価関数には課題が残った． 一方評価関数が， タワー配置がウェーブを攻略できるかどうかの情報しか持たないために，探索は評価関数に基づいたアルゴリズムで行ったが，人間を超える性能は得られなかった．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"AI developed for tower defense (TD) games can be applied to a variety of real-world problems. Therefore, we have been developing a player AI that optimizes the placement of towers in TD. However, there is a problem that the developed player AI can only conquer the maps it has learned. Therefore, as a new approach, we introduce an evaluation function and search to TD's player AI. The evaluation function determines whether a wave can be conquered. As a result, we confirmed that the evaluation function is effective on a board with few towers, but the evaluation function remains problematic when the number of towers increases. On the other hand, since the evaluation function only provides information on whether the tower placement can attack the wave or not, the search was performed by an algorithm based on the evaluation function, but the performance did not exceed that of a human.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"31","bibliographic_titles":[{"bibliographic_title":"ゲームプログラミングワークショップ2024論文集"}],"bibliographicPageStart":"25","bibliographicIssueDates":{"bibliographicIssueDate":"2024-11-15","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}