Optimal policy for minimizing risk models in Markov decision processes
The referred paper deals with the discounted Markov decision processes with countable state space and non-negative bounded general rewards. The attention is focused on the minimizing risk problem, the optimal policy and the optimal values for finite and infinite horizon case. The main results show two sufficient conditions for the existence of an optimal policy in an infinite horizon case. One of them improves an incorrectness existing in the accessible literature. The existence of an optimal policy and the uniqueness of the solution of an optimality equation are shown under the conditions mentioned above.
scientific article; zbMATH DE number 1836739