In this paper we address the problem of incorporating prior knowledge, in the form of causal relations, in causal models. Prior approaches 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.
|Original language||English (US)|
|Title of host publication||ESANN 2011 proceedings, 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning|
|Number of pages||6|
|State||Published - Dec 1 2010|