Bibliografie

(eng): We consider a discrete time Markov reward process with finite state space and assume that the rewards associated with the transitions are random variables with known probability distributions. Formulas for expected value and variance of the cumulative (random) reward are obtained for finite horizon case and infinite horizon models with discounting. Employing the Laurent expansion techniques we obtain explicit formulas for the variance of the long run discounted reward in the terms of undiscounted models.