On Simulating a Markov Chain Stationary Distribution when Transition Probabilities are Unknown

We present an algorithm which, given a n-state Markov chain whose steps can be simulated, outputs a random state whose distribution is within ϵ of the stationary distribution, using O(n)space and O(ϵ-2τ) time, where is a certain “average hitting time” parameter of the chain.