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Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Lear...
Value-function (VF) approximation is a central problem in Reinforcement Learning (RL). Classical non-parametric VF estimation suffers from the curse of dimensionality. As a... -
Leibniz University Hannover
Imported
An efficient data-based off-policy Q-learning algorithm for optimal output fe...
We provide supplementary code material to our recent paper "An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems". The...
