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.
CITATION STYLE
Hofer-Szabó, G. (2018). Bell’s Local Causality is a d-Separation Criterion. In Springer Proceedings in Mathematics and Statistics (Vol. 261, pp. 67–82). Springer New York LLC. https://doi.org/10.1007/978-981-13-2487-1_2
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