Abstract
In recent years the possibility of relaxing the socalled Faithfulness assumption in automated causal
discovery has been investigated. The investigation showed (1) that the Faithfulness assumption
can be weakened in various ways that in an important sense preserve its power, and (2) that weakening of Faithfulness may help to speed up methods based on Answer Set Programming. However,
this line of work has so far only considered the discovery of causal models without latent variables.
In this paper, we study weakenings of Faithfulness
for constraint-based discovery of semi-Markovian
causal models, which accommodate the possibility
of latent variables, and show that both (1) and (2)
remain the case in this more realistic setting