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Title :Extracting Argumentative Dialogues from the Neural Network that Computes the Dungean Argumentation Semantics
Authors :Gotou, Yoshiaki
Hagiwara, Takeshi
Sawamura, Hajime
Issue Date :Jul-2011
Journal Title :7th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'11)
Volume :7
Start Page :28
End Page :33
Abstract :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.
Type Local :会議発表論文
Language :eng
Format :application/pdf
URI :http://hdl.handle.net/10191/25929
fullTextURL :http://dspace.lib.niigata-u.ac.jp/dspace/bitstream/10191/25929/1/7_28-33.pdf
Appears in Collections:99 その他学会発表資料

Please use this identifier to cite or link to this item: http://hdl.handle.net/10191/25929