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• W20470556 startingPage "146" @default.
• W20470556 abstract "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." @default.
• W20470556 created "2016-06-24" @default.
• W20470556 creator A5060777382 @default.
• W20470556 date "2013-11-01" @default.
• W20470556 modified "2023-09-23" @default.
• W20470556 title "Risk-Sensitive and Mean Variance Optimality in Markov Decision Processes" @default.
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• W20470556 hasPublicationYear "2013" @default.
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