mtrl
machin
| mtrl | machin | |
|---|---|---|
| 1 | 2 | |
| 211 | 381 | |
| - | - | |
| 0.0 | 1.8 | |
| over 2 years ago | over 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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mtrl
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Best PyTorch RL library for doing research
MTRL for multi-task RL
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
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Deep-Reinforcement-Learning-Algorithms-with-PyTorch - PyTorch implementations of deep reinforcement learning algorithms and environments
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
tianshou - An elegant PyTorch deep reinforcement learning library.
Apache Impala - Apache Impala
RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
mbrl-lib - Library for Model Based RL
rlpyt - Reinforcement Learning in PyTorch
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥