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cs.LG2022★ 1 cited
Leveraging Reward Gradients For Reinforcement Learning in Differentiable Physics Simulations
Sean Gillen, Katie Byl
In recent years, fully differentiable rigid body physics simulators have been developed, which can be used to simulate a wide range of robotic systems. In the context of reinforcem…
cs.LG2020★ 3 cited
Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning
Sean Gillen, Katie Byl
A key limitation in using various modern methods of machine learning in developing feedback control policies is the lack of appropriate methodologies to analyze their long-term dyn…