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 ...
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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 ...
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Markov Decision Models with Weighted Discounted Criteria

We consider a discrete time Markov Decision Process with infinite horizon. The criterion to be maximized is the sum of a number of standard discounted rewards, each with a different discount factor.