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Introducing directional constraints can drastically enhance the safety-performance balance in reinforcement learning, allowing for more efficient exploration without compromising task success.
SKooP reduces convergence time and boosts performance in legged robot locomotion by leveraging symmetries and advanced Koopman predictions.
