0399099 20240103203308.520131129235959.9 0572-3043 16 s. P cav_un_epca*02970720572-304373 (2013)146-161 Discrete-time Markov decision chains exponential utility functions certainty equivalent mean-variance optimality connections between risk-sensitive and risk-neutral models cav_un_auth*0101196 Sladký Karel Ekonometrie Department of Econometrics E E UTIA-B Department of Econometrics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/E/sladky-0399099.pdf 171396 AVČR a CONACyT CZ cav_un_auth*0307567 GAP402/10/0956 GA ČR cav_un_auth*0263482 GAP402/11/0150 GA ČR cav_un_auth*0273629 In this paper we consider unichain Markov decision processes with finite state space and compact actions spaces where the stream of rewards generated by the Markov processes is evaluated by an exponential utility function with a given risk sensitivity coefficient (so-called risk-sensitive models). If the risk sensitivity coefficient equals zero (risk-neutral case) we arrive at a standard Markov decision process. Then we can easily obtain necessary and sufficient mean reward optimality conditions and the variability can be evaluated by the mean variance of total expected rewards. For the risk-sensitive case we establish necessary and sufficient optimality conditions for maximal (or minimal) growth rate of expectation of the exponential utility function,¨along with mean value of the corresponding certainty equivalent, that take into account not only the expected values of the total reward but also its higher moments. 2014 BB AH RVO:67985556 http://hdl.handle.net/11104/0226807 2013 0572-3043 SCOPUS cav_un_epca*0297072 Acta Oeconomica Pragensia 0572-3043 Roč. 7 č. 3 2013 146 161