Publication details

Optimizing the Expected Mean Payoff in Energy Markov Decision Processes

Authors

BRÁZDIL Tomáš KUČERA Antonín NOVOTNÝ Petr

Type Article in Proceedings
Conference Automated Technology for Verification and Analysis - 14th International Symposium, ATVA 2016
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1007/978-3-319-46520-3_3
Field Informatics
Keywords mean payoff; energy games
Description Energy Markov Decision Processes (EMDPs) are finite-state Markov decision processes where each transition is assigned an integer counter update and a rational payoff. An EMDP configuration is a pair s(n), where s is a control state and n is the current counter value. The configurations are changed by performing transitions in the standard way. We consider the problem of computing a safe strategy (i.e., a strategy that keeps the counter non-negative) which maximizes the expected mean payoff.
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