bibtype K - Conference Paper (Czech conference)
ARLID 0536246
utime 20250123090651.5
mtime 20201215235959.9
WOS 000668460800082
title (primary) (eng) Risk-Sensitivity and Average Optimality in Markov and Semi-Markov Reward Processes
specification
page_count 6 s.
media_type P
serial
ARLID cav_un_epca*0536245
ISBN 978-80-7509-734-7
title Proceedings of the 38th International Conference on Mathematical Methods in Economics
page_num 537-543
publisher
place Brno
name Faculty of Business Economics, Mendel University
year 2020
editor
name1 Kapounek
name2 S.
editor
name1 Vránová
name2 H.
keyword Markov and semi-Markov reward processes
keyword exponential utility function
keyword risk sensitivity
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
share 100
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2020/E/sladky-0536246.pdf
cas_special
project
project_id GA18-02739S
agency GA ČR
ARLID cav_un_auth*0363963
abstract (eng) This contribution is devoted to risk-sensitivity in long-run average optimality of Markov and semi-Markov reward processes. Since the traditional average optimality criteria cannot reflect the variability-risk features of the problem, we are interested in more sophisticated approaches where the stream of rewards generated by the Markov chain that is evaluated by an exponential utility function with a given risk sensitivity coefficient. Recall that for the risk sensitivity coefficient equal to zero (i.e. the so called risk-neutral case) we arrive at traditional optimality criteria, if the risk sensitivity coefficient is close to zero the Taylor expansion enables to evaluate variability of the generated total reward. Observe that the first moment of the total reward corresponds to expectation of total reward and the second central moment to the reward variance. In this note we present necessary and sufficient risk-sensitivity and risk-neutral optimality conditions for long run risk-sensitive average optimality criterion of unichain Markov and semi-Markov reward processes.
action
ARLID cav_un_auth*0395560
name INTERNATIONAL CONFERENCE ON MATHEMATICAL METHODS IN ECONOMICS (MME 2020) /38./
dates 20200909
mrcbC20-s 20200911
place Brno
country CZ
RIV BB
FORD0 50000
FORD1 50200
FORD2 50202
reportyear 2021
num_of_auth 1
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0314173
confidential S
arlyear 2020
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 000668460800082 WOS
mrcbU63 cav_un_epca*0536245 Proceedings of the 38th International Conference on Mathematical Methods in Economics 978-80-7509-734-7 537 543 Brno Faculty of Business Economics, Mendel University 2020
mrcbU67 340 Kapounek S.
mrcbU67 340 Vránová H.