跨越因果层次的概率推理（CS LO）

• 2020 年 1 月 14 日
• 筆記

我们建议将关联、介入和反事实的三层因果层次正式化，作为一系列概率逻辑语言。我们的语言具有严格的表达能力，第一种语言能够表达定量的概率推理——包括条件独立和贝叶斯推理——第二种语言能够编码因果关系的演算推理，第三种语言能够表达任意反事实查询的演算推理。给出了结构因果模型和概率程序上相应的完备的有限公理，并证明了在多项式空间上，每种语言的可满足性和有效性是可判定的。

原文题目：Probabilistic Reasoning across the Causal Hierarchy

原文：We propose a formalization of the three-tier causal hierarchy of association, intervention, and counterfactuals as a series of probabilistic logical languages. Our languages are of strictly increasing expressivity, the first capable of expressing quantitative probabilistic reasoning—including conditional independence and Bayesian inference—the second encoding do-calculus reasoning for causal effects, and the third capturing a fully expressive do-calculus for arbitrary counterfactual queries. We give a corresponding series of finitary axiomatizations complete over both structural causal models and probabilistic programs, and show that satisfiability and validity for each language are decidable in polynomial space.

原文作者：Duligur Ibeling, Thomas Icard

原文地址：https://arxiv.org/abs/2001.02889