  We consider the problem of filtering an unseen Markov chain from noisy
observations, in the presence of uncertainty regarding the parameters of the
processes involved. Using the theory of nonlinear expectations, we describe the
uncertainty in terms of a penalty function, which can be propagated forward in
time in the place of the filter.
