machin
rlpyt
| machin | rlpyt | |
|---|---|---|
| 2 | 4 | |
| 389 | 2,197 | |
| - | - | |
| 1.8 | 0.0 | |
| almost 3 years ago | over 3 years 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
rlpyt
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About Prior Action Distribution in Entropy Regularized Actor-Critic Methods
The above example is from rlpyt library's SAC algorithm.
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Best PyTorch RL library for doing research
I borrow a lot of performance tricks from sample factory, which is awesome but hard to modify from its original APPO algorithm. rlpyt was more modular, and I borrowed more ideas from it (namedarraytuple), but still too limited.
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Spec for RL agent implementation?
rlpyt also has abstractions for additional things besides environments: https://github.com/astooke/rlpyt
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PPO+LSTM Implementation
rlpyt is a library I’m studying right now, could be worth a shot; the code base is somewhat complex but after some reading it’s not so bad :)
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)
gym - A toolkit for developing and comparing reinforcement learning algorithms.
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
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
acme - A library of reinforcement learning components and agents
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
sample-factory - High throughput synchronous and asynchronous reinforcement learning