machin
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ... (by iffiX)
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments (by p-christ)
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machin | Deep-Reinforcement-Learning-Algorithms-with-PyTorch | |
---|---|---|
2 | 2 | |
381 | 5,416 | |
- | - | |
1.8 | 3.6 | |
over 2 years ago | 8 months ago | |
Python | Python | |
MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
machin
Posts with mentions or reviews of machin.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-30.
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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
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
Posts with mentions or reviews of Deep-Reinforcement-Learning-Algorithms-with-PyTorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-07.
-
Frustrated beginner: How to approach/practice implementing papers into code?
This series is actually easier than the David Silver one. Also here is the github repository link - https://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
- Best PyTorch RL library for doing research
What are some alternatives?
When comparing machin and Deep-Reinforcement-Learning-Algorithms-with-PyTorch you can also consider the following projects:
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)
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
Deep-Q-Learning - Tensorflow implementation of Deepminds dqn with double dueling networks
mtrl - Multi Task RL Baselines
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
mbrl-lib - Library for Model Based RL
machin vs stable-baselines3
Deep-Reinforcement-Learning-Algorithms-with-PyTorch vs stable-baselines3
machin vs cleanrl
Deep-Reinforcement-Learning-Algorithms-with-PyTorch vs tianshou
machin vs Apache Impala
Deep-Reinforcement-Learning-Algorithms-with-PyTorch vs cleanrl
machin vs RL-Adventure
Deep-Reinforcement-Learning-Algorithms-with-PyTorch vs Deep-Q-Learning
machin vs tianshou
Deep-Reinforcement-Learning-Algorithms-with-PyTorch vs mtrl
machin vs ElegantRL
Deep-Reinforcement-Learning-Algorithms-with-PyTorch vs mbrl-lib