Thinking About Causation: A Causal Language with Epistemic Operators

In recent years a lot of effort has been put in the development of formal models of causal reasoning. A central motivation behind this is the importance of causal reasoning for AI. Making computers take into account causal information is currently one of the central challenges of AI research [27, 9]. There has also been tremendous progress in this direction after the earlier groundbreaking work in [23] and [28]. Advanced formal and computational tools have been developed for modelling causal reasoning and learning causal information, with applications in many different scientific areas. In this paper we want to extend this work further. The direction we want to explore is that of developing formal models of the interaction between causal and epistemic reasoning.