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Partially Observable Total-Cost Markov Decision Processes with Weakly Continuous Transition Probabilities

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 ...
Nature

Markov Decision Processes and Stochastic Control

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 ...
JSTOR Daily

On the Asymptotic Optimality of Finite Approximations to Markov Decision Processes with Borel Spaces

Mathematics of Operations Research, Vol. 42, No. 4 (November 2017), pp. 945-978 (34 pages) Calculating optimal policies is known to be computationally difficult for Markov decision processes (MDPs) ...
Nature

Probabilistic Model Checking and Markov Decision Processes

Probabilistic model checking and Markov decision processes (MDPs) form two interlinked branches of formal analysis for systems operating under uncertainty. These techniques offer a mathematical ...