On 13 June, 2012, the MCMP is meeting the LMU Stats Department again: "Formal Informal" will center about "The Markov Assumption". Join us for the discussion in an open round at 6:30pm, Alte Bibliothek, room 245 (Ludwigstra├če 33). Presenters will be Conor Mayo-Wilson (CMU Philosophy, currently visitor at the MCMP), Marco Cattaneo (LMU Statistics), and Roland Poellinger (MCMP/LMU).

From the manifesto: Bayesian nets are a powerful means of representing conditional independencies between variables in compact manner. Whatever the size of the domain, consistent inference is facilitated by one simple local requirement: The Markov assumption states that a variable is independent of all other non-successors given the values of its parents in the graph. In causal guise: Direct causes screen off their direct effects from other causal influences. What other ways of reading the Markov assumption are there? Why is it justified? Where does it hold? How can it be bent?

Download the invitation here as a PDF document.