Original title: Cumulative Optimality in Risk-Sensitive and Risk-Neutral Markov Reward Chains
Authors: Sladký, Karel
Document type: Papers
Conference/Event: MME 2013. International Conference on Mathematical Methods in Economics 2013 /31./, Jihlava (CZ), 2013-09-11 / 2013-09-13
Year: 2013
Language: eng
Abstract: This contribution is devoted to risk-sensitive and risk-neutral optimality in Markov decision chains. Since the traditional optimality criteria (e.g. discounted or average rewards) cannot reflect the variability-risk features of the problem, and using the mean variance selection rules that stem from the classical work of Markowitz present some technical difficulties, we are interested in expectation of 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 zero we arrive at¨traditional optimality criteria. In this note we present necessary and sufficient risk-sensitivity and risk-neutral optimality conditions; in detail for unichain models and indicate their generalization to multichain Markov reward chains.
Keywords: dynamic programming; risk analysis and management; stochastic models
Project no.: GA13-14445S (CEP), GAP402/11/0150 (CEP)
Funding provider: GA ČR, GA ČR
Host item entry: Proceedings of the 31st International Conference Mathematical Methods in Economics 2013, ISBN 978-80-87035-76-4

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2013/E/sladky-cumulative optimality in risk-sensitive and risk-neutral markov reward chains.pdf
Original record: http://hdl.handle.net/11104/0222069

Permalink: http://www.nusl.cz/ntk/nusl-155366


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