Informace o publikaci

Conditional Value-at-Risk for Reachability and Mean Payoff in Markov Decision Processes

Autoři

KŘETÍNSKÝ Jan MEGGENDORFER Tobias

Rok publikování 2018
Druh Článek ve sborníku
Konference Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS '18)
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
Doi http://dx.doi.org/10.1145/3209108.3209176
Klíčová slova conditional value-at-risk; Markov chains; Markov decision processes; reachability; mean-payoff
Popis We present the conditional value-at-risk (CVaR) in the context of Markov chains and Markov decision processes with reachability and mean-payoff objectives. CVaR quantifies risk by means of the expectation of the worst p-quantile. As such it can be used to design risk-averse systems. We consider not only CVaR constraints, but also introduce their conjunction with expectation constraints and quantile constraints (value-at-risk, VaR). We derive lower and upper bounds on the computational complexity of the respective decision problems and characterize the structure of the strategies in terms of memory and randomization.
Související projekty:

Používáte starou verzi internetového prohlížeče. Doporučujeme aktualizovat Váš prohlížeč na nejnovější verzi.

Další info