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Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics
http://hdl.handle.net/10191/25929
http://hdl.handle.net/10191/2592977b1cdc8-a9ac-4831-aacd-595195e7e92c
名前 / ファイル | ライセンス | アクション |
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7_28-33.pdf (320.1 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2014-02-28 | |||||
タイトル | ||||||
タイトル | Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_5794 | |||||
タイプ | conference paper | |||||
著者 |
Gotou, Yoshiaki
× Gotou, Yoshiaki× Hagiwara, Takeshi× Sawamura, Hajime |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 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. | |||||
書誌情報 |
7th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'11) en : 7th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'11) 巻 7, p. 28-33, 発行日 2011-07 |
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著者版フラグ | ||||||
値 | author |