In this paper, we introduce a novel causal structure learning algorithm called Endogenous and Exogenous Markov Blankets Intersection (EEMBI), which combines the properties of Bayesian networks and Structural Causal Models (SCM). Furthermore, we propose an extended version of EEMBI, namely EEMBI-PC, which integrates the last step of the PC algorithm into EEMBI.

翻译：本文提出了一种新颖的因果结构学习算法，称为内生与外生马尔可夫毯交集（EEMBI），该算法结合了贝叶斯网络与结构因果模型（SCM）的性质。此外，我们提出了EEMBI的扩展版本即EEMBI-PC，它将PC算法的最后一步集成到EEMBI中。