文章基本信息

标题：Ranking Arguments based on Counter-Transitivity
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作者：Fuan Pu ; Guiming Luo
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：12496-12501
DOI：10.1016/j.ifacol.2017.08.2057
语种：English
出版社：Elsevier
摘要：AbstractThe principle of counter-transitivity plays an important role in argumentation. It states that an argument x is stronger than another argument y, if the attackers of x are weaker than those of y. In this paper, we generalise this principle in order to compare and rank arguments. Two basic criteria, quantity-and quality-based, as well as their various combinations, are proposed to instantiate the principle. Based on these instantiations, a family of argument ranking semantics are then developed and studied. We show that these semantics enjoy different behaviours, and can provide different levels of ranking precision on arguments. Moreover, we reveal that Dung’s classical semantics also satisfy counter-transitivity, and can be seen as a three-level quality-based semantics.
关键词：KeywordsArtificial intelligenceArgumentationLogical designRanking semanticsDecision making