Abstract: Safety guarantee is an important topic when training real-world tasks with reinforcement learning (RL). During online environmental exploration, any constraint violation can lead to ...
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Abstract: This article proposes a data-driven model-free inverse Q-learning algorithm for continuous-time linear quadratic regulators (LQRs). Using an agent’s trajectories of states and optimal ...
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