Judea Pearl has added considerably to this line of thinking (Bayesian Networks), by annotating them with causality. This allows us to explicitly model the tradi

Judea Pearl has added considerably to this line of thinking (Bayesian Networks), by annotating them with causality. This allows us to explicitly model the traditional notion of "hidden variables", or "confounders", and make sound inferences in many (most?) practical cases even when one can't directly observe -- but merely suspect the existence of -- some hidden cause. I thoroughly enjoyed his "The Book of Why", a lay introduction to this subject.