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Reinforcement learning

Reinforcement learning is a machine learning paradigm focused on sequential decision-making, in which an autonomous agent learns optimal behavior by interacting with a dynamic environment to maximize cumulative reward signals.

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annotated_deep_learning_paper_implementations

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  • Updated Jan 22, 2026
  • Python
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github.com/topics/reinforcement-learning
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