Causes and explanations in the structural-model approach
Thomas Eiter, Thomas Lukasiewicz · Uncertainty in Artificial Intelligence · 2002
In this paper, we continue our research on the algorithmic aspects of Halpern and Pearl's causes and explanations in the structural-model approach. To this end, we present new characterizations of weak causes for certain classes of causal models, which show that under suitable restrictions deciding causes and explanations is tractable. To our knowledge, these are the first explicit tractability results for the structural model approach.