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On searching explanatory argumentation graphs

机译:搜索解释性论证图

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Cases or examples can be often explained by the interplay of arguments in favour or against their outcomes. This paper addresses the problem of finding explanations for a collection of cases where an explanation is a labelled argumentation graph consistent with the cases, and a case is represented as a statement labelling. The focus is on semi-abstract argumentation graphs specifying attack and subargument relations between arguments, along with particular complete argument labellings taken from probabilistic argumentation where arguments can be excluded. The framework and computational considerations lead to an iterated local iterative deepening depth-first search to collect ‘interesting’ semi-abstract argumentation graphs consistent with a collection of statement labellings. Finally, the framework is illustrated and evaluated with a proof-of-concept implementation.
机译:案例或示例通常可以通过赞成或反对其结果的参数的相互作用来解释。本文讨论了用于集合的解释的问题,其中说明是与本例一致的标记的参数图,以及案例表示为语句标签。重点是在半抽象的论据图表上,指定参数之间的攻击和子地图关系,以及特定的完整参数签名,从概率论证中取出,其中可以排除参数。框架和计算考虑因素导致迭代的本地迭代深度深度首次搜索,以收集“有趣”的半抽象参数图,这与一系列语句标签一致。最后,用概念验证实现来说明和评估框架。

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