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https://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
https://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
Last synced: 3 months ago
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PyTorch implementations of deep reinforcement learning algorithms and environments
- Host: GitHub
- URL: https://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
- Owner: p-christ
- License: mit
- Created: 2018-09-07T13:01:21.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-08-23T19:03:14.000Z (about 1 year ago)
- Last Synced: 2024-04-20T11:35:49.962Z (7 months ago)
- Language: Python
- Homepage:
- Size: 30.1 MB
- Stars: 5,404
- Watchers: 107
- Forks: 1,180
- Open Issues: 45
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Metadata Files:
- Readme: README.md
- License: LICENSE
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- StarryDivineSky - p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch - 评论家 (SAC) ( Haarnoja et al. 2018 )、离散动作的软演员-评论家 (SAC-Discrete) ( Christodoulou 2019 )、Asynchronous Advantage Actor Critic (A3C) ( Mnih et al. 2016 )、同步优势演员评论家 (A2C)、近端策略优化 (PPO) ( Schulman et al. 2017 )、具有事后经验重放的 DQN (DQN-HER) ( Andrychowicz et al. 2018 )、具有事后经验重放的 DDPG (DDPG-HER) ( Andrychowicz et al. 2018 )、分层 DQN (h-DQN) ( Kulkarni et al. 2016 )、用于分层强化学习 (SNN-HRL) 的随机神经网络 ( Florensa et al. 2017 )、多样性就是你所需要的 (DIAYN) ( Eyensbach et al. 2018 )。所有实现都能够快速解决 Cart Pole(离散动作)、Mountain Car Continuous(连续动作)、Bit Flipping(具有动态目标的离散动作)或 Fetch Reach(具有动态目标的连续动作)。计划添加更多的分层 RL 算法。 (时间序列 / 网络服务_其他)