Asinterventions areexpensive(require carefully controlled experiments) andperforming multiple interventions is time-consuming, an important goal in causal discovery is to design algorithms that utilize simple (preferably, single variable) and fewer interventions [Shanmugam et al.,2015]. However, when there are latents or unobserved variables in the system, in the worst-case, it is not possible to learn the exact causal DAG without intervening on every variable at least once.

Structural Causal Models (SCM) framework introduced by Pearl [2009].

In a graph G a path p is blocked by a set of nodes Z if and only if 1. p

We would like to thank you for your time and valuable feedback. Thank you for helping us to improve our manuscript! We hope to have correctly understood your questions, and will try to exhaustively address all your comments. We agree to be more specific as to what we mean by "other types of interventions" in footnote 1, p. 3, and will We thank reviewer 4 for the additional comments on the manuscript. Combining this method with A-ICP is interesting future work.

Structural Causal Models (SCM) framework introduced by Pearl [2009].