This article introduces a new algorithm based on the damped Newton method for the H tracking control problem of unknown continuous-time nonlinear systems. The algorithm, named model-free Policy Iteration (PI),…
Continue readingThe paper discusses the challenges of offline reinforcement learning (RL) when dealing with imbalanced datasets that are dominated by suboptimal trajectories. It finds that current offline RL algorithms tend to…
Continue readingThe paper introduces Parallel Q-Learning (PQL), a technique that optimizes off-policy reinforcement learning for large-scale GPU-based simulations. PQL is designed to leverage the superior sample efficiency of off-policy learning while…
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