rlpyt
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
| rlpyt | Deep-Reinforcement-Learning-Algorithms-with-PyTorch | |
|---|---|---|
| 4 | 2 | |
| 2,197 | 5,416 | |
| - | - | |
| 0.0 | 3.6 | |
| over 3 years ago | 8 months ago | |
| Python | Python | |
| MIT License | MIT License |
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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 :)
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
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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?
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.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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
Deep-Q-Learning - Tensorflow implementation of Deepminds dqn with double dueling networks
sample-factory - High throughput synchronous and asynchronous reinforcement learning
mtrl - Multi Task RL Baselines