Identifying Independencies in Causal Graphs with Feedback

This addresses a foundational issue in causal inference for researchers dealing with feedback loops, though it is incremental as it extends an existing criterion.

The paper tackled the problem of testing conditional independence in causal graphs with feedback, showing that the d-separation criterion is valid for discrete variables in feedback systems.