0411443 20240103182328.120060210235959.9 Mean variance optimality in Markov decision chains 8 s. Proceedings of the 23rd International Conference Mathematical Methods in Economics 2005350-357978-80-7041-535-1SkalskáH.Hradec KrálovéGadeamus2005 Optimalita prumerne variance v markovskych rozhodovacich procesech Markov reward processes expectation and variance of cumulative rewards cav_un_auth*0101196 Sladký Karel UTIA-B Department of Econometrics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101193 Sitař Milan UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. 12B GA402/05/0115 GA ČR cav_un_auth*0001811 CEZ:AV0Z10750506 In this note, we consider discrete-time Markov decision processes with finite state space. Recalling explicit formulas for the growth rate of expected value and variance of the cumulative (random) reward, algorithmic procedures for finding optimal policies with respect to various mean variance optimality criteria are discussed. Computational experience with large scale numerical examples is reported. V praci se studuji diskretni markovske rozhodovaci procesy s konecnym stavovym prostorem. Vyuzitim explicitnich vztahu pro rychlost rustu ocekavanych hodnot, jakoz i rozptylu kumulativniho (nahodneho) vynosu, jsou navrzeny algorithnmicke postupy pro nalezeni optimalniho rizeni vzhledem k ruznym kriteriim. cav_un_auth*0213243 Mathematical Methods in Economics 2005 /23./ Hradec Králové CZ 14.09.2005-16.09.2005 BB 2010 E http://hdl.handle.net/11104/0131524 2005 Proceedings of the 23rd International Conference Mathematical Methods in Economics 2005 978-80-7041-535-1 350 357 Hradec Králové Gadeamus 2005 Skalská H. 340