论文标题
概率推论：一种概率结构性论证的方法
Probabilistic Deduction: an Approach to Probabilistic Structured Argumentation
论文作者
论文摘要
本文介绍了概率推论（PD）作为概率结构性论证的一种方法。 PD框架由概率规则（P-Rules）组成。作为经典结构化论证框架的规则，P规则形成了扣除系统。此外，P规则还代表了定义关节概率分布的条件概率。使用PD框架，通过解决规则 - 稳定性的满意度来执行概率推理。同时，可以通过争论和攻击来获得概率推理的论点阅读。在这项工作中，我们介绍了封闭世界假设（P-CWA）的概率版本，并证明我们的概率方法与P-CWA下经典论证的完整扩展和最大的熵推理相吻合。我们提出了几种方法来计算P规则中的联合概率分布，以实现PD实用的证明理论。 PD提供了一个框架，可以用论证推理统一概率推理。这是概率结构化论证中的第一项工作，其中未假定联合分布形成外部来源。
This paper introduces Probabilistic Deduction (PD) as an approach to probabilistic structured argumentation. A PD framework is composed of probabilistic rules (p-rules). As rules in classical structured argumentation frameworks, p-rules form deduction systems. In addition, p-rules also represent conditional probabilities that define joint probability distributions. With PD frameworks, one performs probabilistic reasoning by solving Rule-Probabilistic Satisfiability. At the same time, one can obtain an argumentative reading to the probabilistic reasoning with arguments and attacks. In this work, we introduce a probabilistic version of the Closed-World Assumption (P-CWA) and prove that our probabilistic approach coincides with the complete extension in classical argumentation under P-CWA and with maximum entropy reasoning. We present several approaches to compute the joint probability distribution from p-rules for achieving a practical proof theory for PD. PD provides a framework to unify probabilistic reasoning with argumentative reasoning. This is the first work in probabilistic structured argumentation where the joint distribution is not assumed form external sources.
