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Feasibility-Guided Safety-Aware Model Predictive Control for Jump Markov Linear Systems
In this paper, we present a framework that synthesizes maximally safe control policies for Jump Markov Linear Systems subject to stochastic mode switches.
Recursively-Constrained Partially Observable Markov Decision Processes
Evaluations on a set of benchmark problems demonstrate the efficacy of our algorithm and show that policies for RC-POMDPs produce more desirable behaviors than policies for C-POMDPs.
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