用推导图解析因果推断规则，让干预查询更高效
Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
- 用推导图表示do-calculus规则的应用顺序与组合方式
- 仅需最多四步规则应用即可完成因果识别
- 可生成多个等效估计量，提升因果效应估计效率
do-演算定义了一套通用的干预查询推理系统，可通过规则的连续应用转换因果量。这一过程产生丰富的等价干预表达式空间，但规则的组合与排序仍具挑战性。本文提出推导图，用于刻画do-演算规则的应用与组合方式，并表征在do-演算下等价的所有观测与干预概率空间。推导图的结构揭示了一个简单程序，最多只需四次do-演算规则应用。最后，我们证明将识别算法应用于等价因果查询，可生成多个有效估计量，从而获得更高效的因果效应估计器。
原文摘要 · Abstract (English)
The do-calculus defines a general system of inference for interventional queries, allowing causal quantities to be transformed through successive applications of its rules. This process induces a rich space of equivalent interventional expressions, but combining and ordering these rules remains challenging. In this work, we introduce derivation graphs, which represent how do-calculus rules are applied and combined, and characterize the full space of observational and interventional probabilities which are equivalent under the do-calculus. The structure of these graphs yields a simple procedure that uses at most four applications of do-calculus rules. Finally, we show how applying identification algorithms to equivalent causal queries produces multiple valid estimands for the same causal quantity, eventually yielding more efficient estimators.
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