Markov Models

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Visible to the public Safety-Constrained Reinforcement Learning for MDPs

ABSTRACT
Many formal system models are inherently stochastic, consider for instance randomized distributed algorithms (where randomization breaks the symmetry between processes), security (e.g., key generation at encryption), systems biology (where species randomly react depending on their concentration), or embedded systems (interacting with unknown and varying environments).