论文标题
通过特定于上下文的独立关系来识别因果关系
Identifying Causal Effects via Context-specific Independence Relations
论文作者
论文摘要
因果效应识别考虑了是否可以从给定因果结构中的被动观察到的分布中唯一确定介入的概率分布。如果生成系统诱导特定于上下文的独立性（CSI）关系，则基于DO-Calculus的现有识别程序和标准本质上是不完整的。我们表明，在CSIS存在的情况下，确定因果效应非识别性是NP-HARD。在此激励的情况下，我们设计了一个微积分和一个自动搜索程序，以识别CSIS存在的因果影响。该方法是合理的，它包括标准的DO-Calculus作为一种特殊情况。通过该方法，我们可以获得以前无法获得的识别公式，并证明少数CSI关系可能足以将以前的不可识别的实例转化为可识别。
Causal effect identification considers whether an interventional probability distribution can be uniquely determined from a passively observed distribution in a given causal structure. If the generating system induces context-specific independence (CSI) relations, the existing identification procedures and criteria based on do-calculus are inherently incomplete. We show that deciding causal effect non-identifiability is NP-hard in the presence of CSIs. Motivated by this, we design a calculus and an automated search procedure for identifying causal effects in the presence of CSIs. The approach is provably sound and it includes standard do-calculus as a special case. With the approach we can obtain identifying formulas that were unobtainable previously, and demonstrate that a small number of CSI-relations may be sufficient to turn a previously non-identifiable instance to identifiable.
