XinJingHao/DRL-Pytorch
PyTorch implementations of deep reinforcement learning algorithms including Q-learning, DDQN, PER, C51, PPO, DDPG, TD3, and SAC.
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A unified collection of clean, robust PyTorch implementations of popular deep reinforcement learning algorithms. The repository covers value-based methods (Q-learning, Duel DDQN, PER, C51, Noisy DQN), policy gradient methods (PPO for discrete and continuous spaces), and actor-critic algorithms (DDPG, TD3, SAC, ASL). Each algorithm is organized in separate folders with gymnasium-based training examples.
Frequently asked
- What is XinJingHao/DRL-Pytorch?
- PyTorch implementations of deep reinforcement learning algorithms including Q-learning, DDQN, PER, C51, PPO, DDPG, TD3, and SAC.
- Is DRL-Pytorch open source?
- Yes — XinJingHao/DRL-Pytorch is an open-source project tracked on heatdrop.
- What language is DRL-Pytorch written in?
- XinJingHao/DRL-Pytorch is primarily written in Python.
- How popular is DRL-Pytorch?
- XinJingHao/DRL-Pytorch has 3.4k stars on GitHub.
- Where can I find DRL-Pytorch?
- XinJingHao/DRL-Pytorch is on GitHub at https://github.com/XinJingHao/DRL-Pytorch.