提出新渐进语义，让论点可接受性计算更符合直觉且收敛性更强。
Double Rectified Linear Unit-based Modular Semantics for Quantitative Bipolar Argumentation Framework
- 基于双整流线性单元设计模块化语义框架
- 在无环与部分有环结构中均能保证收敛
- 结果更符合直觉，适合需要理性推理的场景
定量双向论证框架（QBAFs）为双向论证框架（BAFs）中的论点可接受性计算提供了一种新方法。每个论点初始赋予强度值，再通过考虑其支持者和攻击者的共同影响更新为最终强度。尽管已有多种语义被提出，但常产生分歧或违反直觉的结果，即使在简单无环情况下亦然。本文提出一种新型渐进语义，使结果更贴近直观预期，同时满足文献中已有的理性后设条件。此外，研究其收敛行为，证明该语义不仅在无环QBAFs中收敛，还适用于更广泛的循环框架类别。
原文摘要 · Abstract (English)
Quantitative Bipolar Argumentation Frameworks (QBAFs) provide an alternative approach to computing argument acceptability in Bipolar Argumentation Frameworks (BAFs). Each argument is assigned an initial strength, which is then updated to a final strength by considering the influence of both its attackers and supporters. Over the years, several semantics have been proposed to compute argument acceptability in QBAFs, yet they often yield divergent or counterintuitive results, even for simple acyclic cases. We introduce novel gradual semantics for QBAFs that address these limitations, producing results that align more closely with intuitive expectations, while satisfying established rationality postulates from the literature. Furthermore, we study its convergence behavior, proving that it converges not only for acyclic QBAFs but also for broader classes of cyclic frameworks.
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