论文标题
通过模态逻辑形式化统计因果关系
Formalizing Statistical Causality via Modal Logic
论文作者
论文摘要
我们提出了一种形式的语言来描述和解释统计因果关系。具体而言，我们定义了统计因果关系语言（STACL），以表达因果关系并指定因果推断的要求。 STACL将模态算子纳入干预措施，以在Kripke模型中不同可能的世界中的概率分布之间表达因果关系。我们使用STACL公式正式将公理制成概率分布，干预措施和因果谓词。这些公理足以得出珍珠圆柱的规则。最后，我们通过示例证明了STACL可用于指定和解释统计因果推断的正确性。
We propose a formal language for describing and explaining statistical causality. Concretely, we define Statistical Causality Language (StaCL) for expressing causal effects and specifying the requirements for causal inference. StaCL incorporates modal operators for interventions to express causal properties between probability distributions in different possible worlds in a Kripke model. We formalize axioms for probability distributions, interventions, and causal predicates using StaCL formulas. These axioms are expressive enough to derive the rules of Pearl's do-calculus. Finally, we demonstrate by examples that StaCL can be used to specify and explain the correctness of statistical causal inference.
