Bell's local causality is a d-separation criterion

This paper aims to motivate Bell's notion of local causality by means of Bayesian networks. In a locally causal theory any superluminal correlation should be screened off by atomic events localized in any so-called \textit{shielder-off region} in the past of one of the correlating events. In a Bayesian network any correlation between non-descendant random variables are screened off by any so-called \textit{d-separating set} of variables. We will argue that the shielder-off regions in the definition of local causality conform in a well defined sense to the d-separating sets in Bayesian networks.Comment: 13 pages, 8 figure

Bell's local causality is a d-separation criterion

This paper aims to motivate Bell’s notion of local causality by means of Bayesian networks. In a locally causal theory any superluminal correlation should be screened off by atomic events localized in any so-called shielder-off region in the past of one of the correlating events. In a Bayesian network any correlation between non-descendant random variables are screened off by any so-called d-separating set of variables. We will argue that the shielder-off regions in the definition of local causality conform in a well defined sense to the d-separating sets in Bayesian networks