{"created":"2025-01-19T01:28:35.498112+00:00","updated":"2025-01-19T11:32:58.671122+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229438","sets":["1164:4061:11136:11366"]},"path":["11366"],"owner":"44499","recid":"229438","title":["ChatGPTを用いた認知アーキテクチャの構想－ユーザーの発話と発話意図に乖離があるケースを例に"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-14"},"_buckets":{"deposit":"d3da3191-fda7-4fe6-99b8-096cc3a1b926"},"_deposit":{"id":"229438","pid":{"type":"depid","value":"229438","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ChatGPTを用いた認知アーキテクチャの構想－ユーザーの発話と発話意図に乖離があるケースを例に","author_link":["617043","617041","617045","617044","617042"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ChatGPTを用いた認知アーキテクチャの構想－ユーザーの発話と発話意図に乖離があるケースを例に"},{"subitem_title":"Conceptualization of Cognitive Architecture using ChatGPT - Studies on Discrepancies between User Utterances and Their 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University","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/229438/files/IPSJ-UBI23080016.pdf","label":"IPSJ-UBI23080016.pdf"},"date":[{"dateType":"Available","dateValue":"2025-11-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-UBI23080016.pdf","filesize":[{"value":"1.0 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正彦"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11838947","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":"2188-8698","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，認知アーキテクチャ (Cognitive Architecture: CA) に基づく汎用人工知能研究が，大規模言語モデル (Large Language Model: LLM) の影響をどのように受けるかを 2 つの問いに基づいて検討する．1 つ目の問いは「RQ1: 大規模言語モデルと認知アーキテクチャを組み合わせることは有効か」である．もう 1 つの問いは「RQ2: どのような方法で組み合わせるのが有効か」である．まず，大規模言語モデルと認知アーキテクチャを組み合わせる方法論として 2 つ提案する．1 つは，LLM Embedded in CA (LEC) であり，設計したアーキテクチャの各モジュールを大規模言語モデルによって実装する．もう 1 つは，CA Embedded in LLM (CEL) であり，プロンプトを工夫することで設計した認知アーキテクチャのような振る舞いを大規模言語モデルにさせる．さらに，信念・願望・意図の 3 つの内部状態から発話生成することを前提とした，検証用対話アーキテクチャを設計した．実験では，発話と発話意図に乖離のあるシチュエーションを 3 つ（皮肉・ツンデレ・社会的制約）用意し，字義通りの意味にとらわれず，言外の意味を理解して応答ができるかを調べた．比較条件は，提案である LEC 条件，CEL 条件のほかに，他の条件との統制をとりつつ元々の大規模言語モデルに近い振る舞いをする LLM 条件と，提案手法と同等な内部表現が与えられる LLM with BDI (LWB) 条件の 4 つとした．結果，LWB 条件では 30% に止まった成功率がアーキテクチャを与えた LEC 条件で 100% に向上したことから，RQ1 に対する結論として大規模言語モデルと認知アーキテクチャを組み合わせることの有効性が認められた．また，RQ2 に対する結論として CEL と比較して LEC は成功率が高い傾向にあり，本実験の範囲では有望であった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ユビキタスコンピューティングシステム（UBI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-11-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"16","bibliographicVolumeNumber":"2023-UBI-80"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229438,"links":{}}