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Optimal Control for Constrained Discrete-Time Nonlinear Systems Based on Safe Reinforcement Learning
Abstract: The state and input constraints of nonlinear systems could greatly impede the realization of their optimal control when using reinforcement learning (RL)-based approaches since the commonly ...
Abstract: We review optimal transport (OT) which can be informally described as “deforming” a source probability distribution into a target probability distribution with minimal cost. OT was ...
We develop a general policy analysis framework for an open economy that features nominal rigidities and financial frictions giving rise to endogenous PPP and UIP deviations. The efficient allocation ...
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