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Reinforcement Learning on ML1

Reinforcement Learning on ML1

4Environment Steps (M)SAC

Updated 4mo ago

Evaluation results

Method	Links
SAC2025.03		4
TOP-ERL2025.03		4
T-SAC2025.03		1

State-of-the-art paper

SAC

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Dataset

ML1

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Related benchmarks

Reinforcement Learning on Box-Pushing dense Robotic Manipulation on Box-Pushing dense (max 20M steps)Robotic Manipulation on Box-Pushing sparse (max 20M steps)Meta-Reinforcement Learning on Meta-World ML1 max 5M steps Reinforcement Learning on Box-Pushing sparse

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