Název:
Risk-Sensitive Optimality in Markov Games
Autoři:
Sladký, Karel ; Martínez Cortés, V. M. Typ dokumentu: Příspěvky z konference Konference/Akce: MME 2017. International Conference Mathematical Methods in Economics /35./, Hradec Králové (CZ), 20170913
Rok:
2017
Jazyk:
eng
Abstrakt: The article is devoted to risk-sensitive optimality in Markov games. Attention is focused on Markov games evolving on communicating Markov chains with two-players with opposite aims. Considering risk-sensitive optimality criteria means that total reward generated by the game is evaluated by exponential utility function with a given risk-sensitive coefficient. In particular, the first player (resp. the secondplayer) tries to maximize (resp. minimize) the long-run risk sensitive average reward. Observe that if the second player is dummy, the problem is reduced to finding optimal policy of the Markov decision chain with the risk-sensitive optimality. Recall that for the risk sensitivity coefficient equal to zero we arrive at traditional optimality criteria. In this article, connections between risk-sensitive and risk-neutral Markov decisionchains and Markov games models are studied using discrepancy functions. Explicit formulae for bounds on the risk-sensitive average long-run reward are reported. Policy iteration algorithm for finding suboptimal policies of both players is suggested. The obtained results are illustrated on numerical example.
Klíčová slova:
communicating Markov chains; dynamic programming; risk-sensitive optimality; two-person Markov games Číslo projektu: GA13-14445S (CEP) Poskytovatel projektu: GA ČR Zdrojový dokument: Proceedings of the 35th International Conference Mathematical Methods in Economics (MME 2017), ISBN 978-80-7435-678-0