bibtype C - Conference Paper (international conference)
ARLID 0583660
utime 20250131155210.8
mtime 20240305235959.9
ISBN 978-80-213-3126-6
WOS 000936369700074
title (primary) (eng) Central Moments and Risk-Sensitive Optimality in Markov Reward Processes
publisher
place Praha
name Czech University of Life Sciences Prague
pub_time 2021
specification
page_count 6 s.
media_type P
serial
ARLID cav_un_epca*0546142
ISBN 978-80-213-3126-6
title MME 2021, 39th International Conference on Mathematical Methods in Economics. Conference Proceedings
page_num 446-451
publisher
place Prague
name Faculty of Economics and Management, Czech University of Life Sciences Prague
year 2021
editor
name1 Hlavatý
name2 R.
keyword discrete- and continuous-time Markov reward chains
keyword exponential utility
keyword moment generating functions
author (primary)
ARLID cav_un_auth*0101196
name1 Sladký
name2 Karel
institution UTIA-B
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2024/E/sladky-0583660.pdf
cas_special
project
project_id GA18-02739S
agency GA ČR
ARLID cav_un_auth*0363963
abstract (eng) In this note we consider discrete- and continuous-time Markov decision processes with finite state space. There is no doubt that usual optimality criteria examined in the literature on optimization of Markov reward processes, e.g. total discounted or mean reward, may be quite insufficient to select more sophisticated criteria that reflect also the variability-risk features of the problem. In this note we focus on models where the stream of rewards generated by the Markov process is evaluated by an exponential utility function with a given risk sensitivity coefficient (so-called risk-sensitive models).For the risk sensitive case, i.e. if the considered risk-sensitivity coefficient is non-zero, we establish explicit formulas for growth rate of expectation of the exponential utility function. Recall that in this case along with the total reward also it higher moments are taken into account. Using Taylor expansion of the utility function we present explicit formulas for calculating variance a higher central moments of the total reward generated by the |Markov reward process along with its asymptotic behaviour.
action
ARLID cav_un_auth*0414661
name MME 2021: International Conference on Mathematical Methods in Economics /39./
dates 20210908
mrcbC20-s 20210910
place Prague
country CZ
RIV BB
FORD0 10000
FORD1 10100
FORD2 10103
reportyear 2024
num_of_auth 1
presentation_type PR
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0352094
confidential S
mrcbC86 Proceedings Paper Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods
arlyear 2021
mrcbU02 C
mrcbU10 2021
mrcbU10 Praha Czech University of Life Sciences Prague
mrcbU12 978-80-213-3126-6
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 000936369700074 WOS
mrcbU63 cav_un_epca*0546142 MME 2021, 39th International Conference on Mathematical Methods in Economics. Conference Proceedings Faculty of Economics and Management, Czech University of Life Sciences Prague 2021 Prague 446 451 978-80-213-3126-6
mrcbU67 Hlavatý R. 340