Possibilities of solution in stochastic decision models with recursive reward functions

A stochastic decision model with general, non-necessarily additive reward function is considered and essential properties of such reward functions are formulated which only allow a successive proceeding in the sense of dynamic programming. Conditions for recursive—additive reward functions are given which ensure the existence of optimal strategies and the usability of value iteration to find an optimal policy and the optimal total reward.