In this article, we tackle the problem of efficiently recomputing the skeptical acceptance of dynamic argumentation frameworks under the well-known preferred semantics. We discuss an incremental algorithmic solution whose main idea is that of exploiting the initial knowledge (including the update to perform) in order to identify a potentially small portion of the argumentation framework. Such a portion is sufficient to compute the skeptical preferred acceptance of a goal argument w.r.t. the whole updated framework. We also discuss on how similar ideas extend to more general argumentation frameworks.

中文翻译：

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动态议论框架中的渐进式怀疑首选接受

在本文中，我们解决了在众所周知的首选语义下有效地重新计算对动态论证框架的怀疑接受的问题。我们讨论一种增量算法解决方案，其主要思想是利用初始知识（包括要执行的更新）来确定论证框架的一小部分。这部分足以计算整个更新框架对目标论点的怀疑首选接受程度。我们还将讨论类似的想法如何扩展到更通用的论证框架。