We consider a finite-state, finite-action, infinite-horizon, discounted reward Markov decision process and study the bias and variance in the value function estimates that result from empirical estimates of the model parameters. We provide closed-form approximations for the bias and variance,...

We consider a finite two-player zero-sum game with vector-valued rewards. We study the question of whether a given polyhedral set D is "approachable," that is, whether Player 1 (the "decision maker") can guarantee that the long-term average reward belongs to D, for any strategy of Player 2 (the...