A constraint-based approach to incorporate prior knowledge in causal models

In this paper we address the problem of incorporating prior knowledge, in the form of causal relations, in causal models. Prior ap- proaches mostly consider knowledge about the presence or absence of edges in the model. We use the formalism of Maximal Ancestral Graphs (MAGs) and adapt cSAT+ to solve this problem, an algorithm for reasoning with datasets defined over different variable sets.