The Complexity of Unobservable Nite-horizon Markov Decision Processes

Abstract

Markov Decision Processes (MDPs) model controlled stochastic systems. Like Markov chains, an MDP consists of states and probabilistic transitions; unlike Markov chains, there is assumed to be an outside controller who chooses an action (with its associated transition matrix) at each step of the process, according to some strategy or policy. In addition… (More)

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