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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F13%3A00399099%21RIV14-GA0-67985556
rdf:type
n5:Vysledek skos:Concept
dcterms:description
In this paper we consider unichain Markov decision processes with finite state space and compact actions spaces where the stream of rewards generated by the Markov processes is evaluated by an exponential utility function with a given risk sensitivity coefficient (so-called risk-sensitive models). If the risk sensitivity coefficient equals zero (risk-neutral case) we arrive at a standard Markov decision process. Then we can easily obtain necessary and sufficient mean reward optimality conditions and the variability can be evaluated by the mean variance of total expected rewards. For the risk-sensitive case we establish necessary and sufficient optimality conditions for maximal (or minimal) growth rate of expectation of the exponential utility function,along with mean value of the corresponding certainty equivalent, that take into account not only the expected values of the total reward but also its higher moments. In this paper we consider unichain Markov decision processes with finite state space and compact actions spaces where the stream of rewards generated by the Markov processes is evaluated by an exponential utility function with a given risk sensitivity coefficient (so-called risk-sensitive models). If the risk sensitivity coefficient equals zero (risk-neutral case) we arrive at a standard Markov decision process. Then we can easily obtain necessary and sufficient mean reward optimality conditions and the variability can be evaluated by the mean variance of total expected rewards. For the risk-sensitive case we establish necessary and sufficient optimality conditions for maximal (or minimal) growth rate of expectation of the exponential utility function,along with mean value of the corresponding certainty equivalent, that take into account not only the expected values of the total reward but also its higher moments.
dcterms:title
Risk-Sensitive and Mean Variance Optimality in Markov Decision Processes Risk-Sensitive and Mean Variance Optimality in Markov Decision Processes
skos:prefLabel
Risk-Sensitive and Mean Variance Optimality in Markov Decision Processes Risk-Sensitive and Mean Variance Optimality in Markov Decision Processes
skos:notation
RIV/67985556:_____/13:00399099!RIV14-GA0-67985556
n5:predkladatel
n7:ico%3A67985556
n3:aktivita
n16:P n16:I
n3:aktivity
I, P(GAP402/10/0956), P(GAP402/11/0150)
n3:cisloPeriodika
3
n3:dodaniDat
n10:2014
n3:domaciTvurceVysledku
n18:6105955
n3:druhVysledku
n17:J
n3:duvernostUdaju
n4:S
n3:entitaPredkladatele
n14:predkladatel
n3:idSjednocenehoVysledku
103023
n3:idVysledku
RIV/67985556:_____/13:00399099
n3:jazykVysledku
n13:eng
n3:klicovaSlova
Discrete-time Markov decision chains; exponential utility functions; certainty equivalent; mean-variance optimality; connections between risk-sensitive and risk-neutral models
n3:klicoveSlovo
n9:exponential%20utility%20functions n9:certainty%20equivalent n9:connections%20between%20risk-sensitive%20and%20risk-neutral%20models n9:Discrete-time%20Markov%20decision%20chains n9:mean-variance%20optimality
n3:kodStatuVydavatele
CZ - Česká republika
n3:kontrolniKodProRIV
[5C5E66D0C336]
n3:nazevZdroje
Acta Oeconomica Pragensia
n3:obor
n15:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n11:GAP402%2F11%2F0150 n11:GAP402%2F10%2F0956
n3:rokUplatneniVysledku
n10:2013
n3:svazekPeriodika
7
n3:tvurceVysledku
Sladký, Karel
s:issn
0572-3043
s:numberOfPages
16