A divide-and-conquer method for computing preferred extensions of argumentation frameworks

Huan Zhang, Songmao Zhang
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Abstract

In this paper, we propose a divide-and-conquer method for solving the preferred extensions enumeration prob-lem, which is computationally intractable in argumentation frameworks. The rationale is to take advantage of the fact that for acyclic argumentation frameworks the computation becomes tractable with polynomial time. Concretely, we identify sufficient conditions for decomposing an argumentation framework into sub-frameworks based on certain cycles, where the soundness and completeness in computing preferred extensions are proved. Based on this conclusion, we devise the partitioning algorithm and carry out an evaluation on the International Competition on Computational Models of Argumentation (ICCMA) 2019 dataset. The results show that for the complex, time-consuming tasks our method could reduce running time when compared with the state-of-the-art solver in ICCMA. This is our first attempt in tackling the complex argumentative knowledge and many directions are yet to be explored, both theoretical and empirical.
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一种计算论证框架优选扩展的分治法
本文提出了一种分而治之的方法来解决在论证框架中难以计算的首选扩展枚举问题。其基本原理是利用了这样一个事实,即对于非循环论证框架,计算在多项式时间内变得易于处理。具体地说,我们确定了基于一定循环将论证框架分解为子框架的充分条件,并证明了计算优选扩展的完备性和完全性。基于这一结论,我们设计了分区算法,并对2019年国际论证计算模型竞赛(ICCMA)数据集进行了评估。结果表明,对于复杂、耗时的任务,与ICCMA中最先进的求解器相比,我们的方法可以减少运行时间。这是我们在处理复杂的论证性知识方面的第一次尝试,许多方向还有待探索,无论是理论还是经验。
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