Bibliography

(eng): We investigate how the mean variance selection rule can work in Markovian decision models. In contrast to the classical models we assume that instead of maximizing the mean reward per transition we consider more sophisticated criteria taking into account also higher moments and the variance of the cumulative reward. Properties of optimal policies as well as optimization procedures with respect to the above criteria are discussed primarily for undiscounted long run models.