bibtype	A - Abstract
ARLID	0410870
utime	20240103182245.1
mtime	20060210235959.9
title (primary) (eng)	Minimum variance criterion in stochastic dynamic programming. Abstract
publisher	place Edinburgh name UK Operational Research Society pub_time 2002
specification	page_count 1 s.
serial	title International Federation of Operational Research Societies 2002. IFORS 2002. Abstracts page_num 28
keyword	stochastic dynamic programming
keyword	Markov decision chains
keyword	mean-variance
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 GA402/01/0539 agency GA ČR ARLID cav_un_auth*0008959 research CEZ:AV0Z1075907 abstract (eng) We investigate how the minimum variance criterion can work in discrete stochastic dynamic programming. We adapt notions and notation used in Markov decision chains and in contrast to the classical models we also consider variance of the obtained total reward. Alternative definitions of the reward variance along with their mutual connections are discussed. Attention is also focused on finding policies minimizing the average reward variance on condition that the average reward is not less than a given value. action ARLID cav_un_auth*0212941 name IFORS 2002 place Edinburgh country GB dates 08.07.2002-12.07.2002 RIV BB department E permalink http://hdl.handle.net/11104/0130957 ID_orig UTIA-B 20020084 arlyear 2002 mrcbU10 2002 mrcbU10 Edinburgh UK Operational Research Society mrcbU63 International Federation of Operational Research Societies 2002. IFORS 2002. Abstracts 28