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.
@article{arxiv.1607.00678,
title = {Optimizing the Expected Mean Payoff in Energy Markov Decision Processes},
author = {Tomáš Brázdil and Antonín Kučera and Petr Novotný},
journal= {arXiv preprint arXiv:1607.00678},
year = {2016}
}
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Full version of a paper published in proceedings of ATVA'16