Contractivity of Bellman operator in risk averse dynamic programming with infinite horizon

The paper deals with a risk averse dynamic programming problem infinite horizon. First, the required assumptions are formulated to have well defined. Then Bellman equation is derived, which may be also seen as standalone reinforcement learning problem. fact that operator contraction proved, guaranteeing convergence of various solution algorithms used for problems, we demonstrate on value iteration and policy algorithms.