比较不确定规则与前提下的结构化论证框架表达能力。
Comparative Expressivity for Structured Argumentation Frameworks with Uncertain Rules and Premises
- 从规则和前提出发建模论证不确定性，统一抽象与结构框架的表达性分析。
- 证明了结构化框架在某些条件下比抽象框架表达能力更强或更弱。
- 适用于研究不确定论证的理论基础，尤其适合逻辑与人工智能方向读者。
在形式化论证中建模定性不确定性对实际应用和理论理解都至关重要。然而，现有研究大多聚焦于不确定情况下的抽象论证模型。受近期文献趋势启发，本文探讨这些抽象模型在合理实例化方面的开放问题。为此，我们将论证的不确定性根植于其组成部分——规则与前提的结构化设定中。主要技术贡献包括：(i) 引入一种可处理抽象与结构化形式系统的表达性概念；(ii) 提出正负表达性结果，系统比较抽象与结构化论证框架在不确定性下的表达能力。这些结果涉及不完整的抽象论证框架及其依赖扩展（在抽象侧），以及ASPIC+（在结构化侧）。
原文摘要 · Abstract (English)
Modelling qualitative uncertainty in formal argumentation is essential both for practical applications and theoretical understanding. Yet, most of the existing works focus on \textit{abstract} models for arguing with uncertainty. Following a recent trend in the literature, we tackle the open question of studying plausible instantiations of these abstract models. To do so, we ground the uncertainty of arguments in their components, structured within rules and premises. Our main technical contributions are: i) the introduction of a notion of expressivity that can handle abstract and structured formalisms, and ii) the presentation of both negative and positive expressivity results, comparing the expressivity of abstract and structured models of argumentation with uncertainty. These results affect incomplete abstract argumentation frameworks, and their extension with dependencies, on the abstract side, and ASPIC+, on the structured side.
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