Long-Term Values in Markov Decision Processes and Repeated Games, and a New Distance for Probability Spaces

We study long-term Markov decision processes (MDPs) and gambling houses, with applications to any partial observation MDPs with finitely many states and zero-sum repeated games with an informed controller.