This paper describes sufficient conditions for the existence of optimal policies for partially observable Markov decision processes (POMDPs) with Borel state, observation, and action sets, when the ...
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 ...
Research interests: Autonomy for Aerospace Systems, Reinforcement Learning, Partially Observable Markov Decision Processes (POMDPs), Stochastic Games Zachary Sunberg is an Assistant Professor in the ...
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