mbrl-lib
rlpyt
mbrl-lib | rlpyt | |
---|---|---|
1 | 4 | |
911 | 2,197 | |
1.9% | - | |
3.4 | 0.0 | |
9 months ago | over 3 years ago | |
Python | Python | |
MIT License | MIT License |
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mbrl-lib
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Best PyTorch RL library for doing research
MBRL-Lib for model-based RL
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?
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
tianshou - An elegant PyTorch deep reinforcement learning library.
Deep-Reinforcement-Learning-Algorithms-with-PyTorch - PyTorch implementations of deep reinforcement learning algorithms and environments
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
acme - A library of reinforcement learning components and agents
mtrl - Multi Task RL Baselines
sample-factory - High throughput synchronous and asynchronous reinforcement learning