Question: Consider the query P(Rain(Sprink1er = true, WetGrass = true) in Figure (a) and how MCMC can answer it.
a. How many states does the Markov chain have?
b. Calculate the transition matrix Q containing q(y + y') for all y, y'.
c. What does Q~, the square of the transition matrix, represent?
d. What about Qn as n -t GO?
e. Explain how to do probabilistic inference in Bayesian networks, assuming that Qn is available. Is this a practical way to do inference?