{"created":"2021-03-01T06:36:59.324899+00:00","id":30878,"links":{},"metadata":{"_buckets":{"deposit":"ec3e56bd-053a-4444-bce5-f4c06441f301"},"_deposit":{"id":"30878","owners":[],"pid":{"revision_id":0,"type":"depid","value":"30878"},"status":"published"},"_oai":{"id":"oai:niigata-u.repo.nii.ac.jp:00030878","sets":["423:435:436","453:457"]},"item_8_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2011-07","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"33","bibliographicPageStart":"28","bibliographicVolumeNumber":"7","bibliographic_titles":[{"bibliographic_title":"7th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'11)"},{"bibliographic_title":"7th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'11)","bibliographic_titleLang":"en"}]}]},"item_8_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Argumentation is a leading principle both foundationally and functionally for agent-oriented computing where reasoning accompanied by communication plays an essential role in agent interaction. We constructed a simple but versatile neural network for neural network argumentation, so that it can decide which argumentation semantics (admissible, stable, semistable, preferred, complete, and grounded semantics) a given set of arguments falls into, and compute argumentation semantics via checking. In this paper, we are concerned with the opposite direction from neural network computation to symbolic argumentation/dialogue. We deal with the question how various argumentation semantics can have dialectical proof theories, and describe a possible answer to it by extracting or generating symbolic dialogues from the neural network computation under various argumentation semantics.","subitem_description_type":"Abstract"}]},"item_8_select_19":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_select_item":"author"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Gotou, Yoshiaki"}],"nameIdentifiers":[{"nameIdentifier":"168696","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Hagiwara, Takeshi"}],"nameIdentifiers":[{"nameIdentifier":"168697","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Sawamura, Hajime"}],"nameIdentifiers":[{"nameIdentifier":"168698","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-08-26"}],"displaytype":"detail","filename":"7_28-33.pdf","filesize":[{"value":"320.1 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"7_28-33.pdf","url":"https://niigata-u.repo.nii.ac.jp/record/30878/files/7_28-33.pdf"},"version_id":"599cfb9c-8f99-4bd6-aed3-6b77fab51ce1"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics"},{"subitem_title":"Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics","subitem_title_language":"en"}]},"item_type_id":"8","owner":"1","path":["457","436"],"pubdate":{"attribute_name":"公開日","attribute_value":"2014-02-28"},"publish_date":"2014-02-28","publish_status":"0","recid":"30878","relation_version_is_last":true,"title":["Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-15T04:01:22.828235+00:00"}