Publication details

Optimizing the Expected Mean Payoff in Energy Markov Decision Processes

Authors

BRÁZDIL Tomáš KUČERA Antonín NOVOTNÝ Petr

Year of publication 2016
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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