Value Iteration and Rolling Plans for Markov Control Processes with Unbounded Rewards

This paper studies the convergence of value-iteration functions and the existence of error bounds for rolling horizon procedures in discrete-time Markov control processes with Borel state and control spaces, and unbounded reward functions with a discount factor.