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Found 3 papers, 2 papers with code
Latent Exploration for Reinforcement Learning
In the PyBullet locomotion tasks, Lattice-SAC achieves state of the art results, and reaches 18% higher reward than unstructured exploration in the Humanoid environment.
DMAP: a Distributed Morphological Attention Policy for Learning to Locomote with a Changing Body
Learning to locomote when the length and the thickness of different body parts vary is challenging, as the control policy is required to adapt to the morphology to successfully balance and advance the agent.
Measuring and modeling the motor system with machine learning
The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data.
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