SLM Lab Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book Foundations of Deep Reinforcement Learning . Documentation · Benchmark Results NOTE: v5.0 updates to Gymnasium, uv tooling, and modern dependencies with ARM support see CHANGELOG.md. Book readers: git checkout v4.1.1 for Foundations of Deep Reinforcement Learning code. : : : : : : : : BeamRider Breakout KungFuMaster MsPacman Pong Qbert Seaquest Sp.Invaders Ant HalfCheetah Hopper Humanoid Inv.DoublePendulum InvertedPendulum Reacher Walker SLM Lab is a software framework for reinforcement learning (RL) research and application in PyTorch. RL trains agents to make decisions by learning from trial and error—like teaching a robot to walk or an AI to play games. What SLM Lab Offers Feature Description Ready to use algorithms PPO, SAC, DQN, A2C, REINFORCE—validated on 70+ environments Easy configuration JSON spec files fully define experiments—no code changes needed Reproducibility Every run saves its spec + git SHA for exact reproduction Automatic analysis Training curves, metrics, and TensorBoard logging out of the box Cloud integration dstack for GPU training, HuggingFace for sharing results…
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