Název:
Risk-Sensitive and Average Optimality in Markov Decision Processes
Autoři:
Sladký, Karel Typ dokumentu: Příspěvky z konference Konference/Akce: 30th International Conference Mathematical Methods in Economics 2012, Karviná (CZ), 2012-09-11 / 2012-09-13
Rok:
2012
Jazyk:
eng
Abstrakt: This contribution is devoted to the risk-sensitive optimality criteria in finite state Markov Decision Processes. At first, we rederive necessary and sufficient conditions for average optimality of (classical) risk-neutral unichain models. This approach is then extended to the risk-sensitive case, i.e., when expectation of the stream of one-stage costs (or rewards) generated by a Markov chain is evaluated by an exponential utility function. We restrict ourselves on irreducible or unichain Markov models where risk-sensitive average optimality is independent of the starting state. As we show this problem is closely related to solution of (nonlinear) Poissonian equations and their connections with nonnegative matrices.
Klíčová slova:
dynamic programming; risk analysis and management; stochastic models Číslo projektu: GAP402/10/0956 (CEP), GAP402/11/0150 (CEP) Poskytovatel projektu: GA ČR, GA ČR Zdrojový dokument: Proceedings of 30th International Conference Mathematical Methods in Economics 2012, ISBN 978-80-7248-779-0