Markov decision processes (MDPs) and stochastic control constitute pivotal frameworks for modelling decision-making in systems subject to uncertainty. At their core, MDPs provide a structured means to ...
We identify a rich class of finite-horizon Markov decision problems (MDPs) for which the variance of the optimal total reward can be bounded by a simple linear function of its expected value. The ...
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