论文标题
跨因果层次结构的概率推理
Probabilistic Reasoning across the Causal Hierarchy
论文作者
论文摘要
我们建议将三层因果关系层次结构形式化为关联，干预和反事实，作为一系列概率的逻辑语言。我们的语言严格提高表达性，第一种能够表达定量概率推理（包括有条件的独立性和贝叶斯推论）的第二种编码DO-Calculus造成因果效应的推理，而第三个则捕获了完全表达的DO-Calculus，以进行任意反事实怪癖。我们在结构性因果模型和概率程序上提供了相应的一系列限制性公理，并表明每种语言的满意度和有效性在多项式空间中都是可决定的。
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.
