machin
mbrl-lib
machin | mbrl-lib | |
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2 | 1 | |
389 | 913 | |
- | 2.0% | |
1.8 | 3.4 | |
almost 3 years ago | 10 months ago | |
Python | Python | |
MIT License | MIT License |
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machin
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Best PyTorch RL library for doing research
Machin is really nice, it is very easy to use and to try different things, although it’s developed by one person and maybe not appropriately tested yet.
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Is there a consensus about RL frameworks?
I found this repo very helpful to get started: https://github.com/iffiX/machin
mbrl-lib
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Best PyTorch RL library for doing research
MBRL-Lib for model-based RL
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Apache Impala - Apache Impala
tianshou - An elegant PyTorch deep reinforcement learning library.
RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
Deep-Reinforcement-Learning-Algorithms-with-PyTorch - PyTorch implementations of deep reinforcement learning algorithms and environments
rlpyt - Reinforcement Learning in PyTorch
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
mtrl - Multi Task RL Baselines