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A Pocket Guide to Reinforcement Learning
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This is an introductory book on reinforcement learning, covering from basic concepts to algorithm implementations. It includes various algorithm implementations based on PyTorch, such as Monte Carlo, PPO, etc., as well as detailed derivations and rigorous proofs of dynamic programming algorithms.
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