RL Policy Trained in 78 Seconds Transfers Successfully to Mujoco
yacineMTB · x · 2026-08-30
The author demonstrates a reinforcement learning policy trained on a custom simulator (dingsim), exhibiting movement behavior that appears to exploit the environment. Crucially, this behavior transfers successfully to the Mujoco CPU environment, validating the sim2real pipeline. The author notes the training was completed in just 78 seconds.
Related event: RL Locomotion Policy Trained in 78 Seconds on Custom Simulator(2 posts)→
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