bibtype	A - Abstract
ARLID	0410871
utime	20240103182245.2
mtime	20060210235959.9
title (primary) (eng)	Optimal solution for undiscounted variance penalized Markov decision chains. Abstract
publisher	place Berlin name HumboldtUniversity Berlin pub_time 2002
specification	page_count 1 s.
serial	title Mathematical Methods in Economy and Industry. Abstracts page_num 14
keyword	Markov decision chains
keyword	optimal policies
keyword	mean-variance penalization
author (primary)	ARLID cav_un_auth*0101196 name1 Sladký name2 Karel institution UTIA-B full_dept Department of Econometrics fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI	12B
cas_special	project project_id GA402/02/1015 agency GA ČR ARLID cav_un_auth*0000527 project project_id GA402/02/0539 agency GA ČR ARLID cav_un_auth*0212942 research CEZ:AV0Z1075907 abstract (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. action ARLID cav_un_auth*0212934 name Joint Czech-German-Slovak Conference /12./ place Arnstadt country DE dates 22.07.2002-26.07.2002 RIV BB department E permalink http://hdl.handle.net/11104/0130958 ID_orig UTIA-B 20020085 arlyear 2002 mrcbU10 2002 mrcbU10 Berlin HumboldtUniversity Berlin mrcbU63 Mathematical Methods in Economy and Industry. Abstracts 14