{"updated":"2025-01-20T00:18:57.259480+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00192065","sets":["6164:6165:6210:9595"]},"path":["9595"],"owner":"44499","recid":"192065","title":["トレーディングカードゲームにおけるデッキ作成とエージェント構築を目標としたニューラルネットを用いた学習モデルの検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-11-05"},"_buckets":{"deposit":"e1daf993-c09f-4ea1-87df-462b9fb16ae7"},"_deposit":{"id":"192065","pid":{"type":"depid","value":"192065","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"トレーディングカードゲームにおけるデッキ作成とエージェント構築を目標としたニューラルネットを用いた学習モデルの検討","author_link":["445316","445318","445315","445317"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"トレーディングカードゲームにおけるデッキ作成とエージェント構築を目標としたニューラルネットを用いた学習モデルの検討"},{"subitem_title":"Consideration of Learning Model with Neural Network to Build Decks and Develop Agents in Trading Card Game","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"不完全情報ゲーム","subitem_subject_scheme":"Other"},{"subitem_subject":"トレーディングカードゲーム","subitem_subject_scheme":"Other"},{"subitem_subject":"ニューラルネットワーク","subitem_subject_scheme":"Other"},{"subitem_subject":"強化学習","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2018-11-05","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"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Meiji 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/192065/files/IPSJ-GPWS2018020.pdf","label":"IPSJ-GPWS2018020.pdf"},"date":[{"dateType":"Available","dateValue":"2018-11-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-GPWS2018020.pdf","filesize":[{"value":"1.2 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":"fbccdab5-b60f-4640-9b31-ae7e2c332338","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山田, 豊大"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"阿原, 一志"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Atsuhiro, Yamada","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kazushi, Ahara","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":"不完全情報ゲームの1種であるトレーディングカードゲーム (TCG) は，デッキ（ゲームに使用するカードセット）をプレイヤーが選択できるなど，囲碁や将棋，その他ボードゲームにはないゲーム要素が特徴であり，強い，又は人間らしいエージェントの作成等の研究には意義があると考えられる．本稿は，単純化されたTCGで，デッキ作成，またエージェントの構築に関する知見を得ることを目標とし，その第一段階としてランダムに与えられたデッキに対してニューラルネットワークを用いた強化学習の有効性について考察した．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Trading Card Game (TCG), one of an incomplete information game, has characteristic features. For example, any player can choose cards they use in their deck. Therefore, it will be significant to study how we obtain a smart or a believable agent. In this paper, we set goals to gain the knowledge of building decks and developing agent in simplified TCG. As the first step, we considered the effectivity of Neural Network by applying that to the game where both players are given random decks.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"132","bibliographic_titles":[{"bibliographic_title":"ゲームプログラミングワークショップ2018論文集"}],"bibliographicPageStart":"128","bibliographicIssueDates":{"bibliographicIssueDate":"2018-11-09","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2018"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T00:57:49.751140+00:00","id":192065,"links":{}}