RockRL
Reinforcement Learning library for public, for now, it only supports TensorFlow.
Installation
pip install rockrl
Environment requirements
RL algorithms are implemented to support gymnasium==0.29.1 version. Main requirements are that:
env.reset()would returnstateandinfostates.env.step(action)would returnstate,reward,terminated,truncated,infostates.
Supported Algorithms
- PPO (Discrete and Continuous)
Code Examples
Proximal Policy Optimization (PPO):
RockRL/tensorflow/examples/ppo/LunarLander-v2/LunarLander-v2.pyis an example of using PPO to solve LunarLander-v2 (Discrete) environment.RockRL/tensorflow/examples/ppo/BipedalWalker-v3/BipedalWalker-v3.pyis an example of using PPO to solve BipedalWalker-v2 (Continuous) environment.RockRL/tensorflow/examples/ppo/BipedalWalkerHardcore-v3/BipedalWalkerHardcore-v3.pyis an example of using PPO to solve BipedalWalker-v3 Hardcore (Continuous) environment.
1 maintainer
Metadata
1 maintainer
Release files for rockrl 0.4.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| rockrl-0.4.6.tar.gz | 13.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rockrl-0.4.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.5 kB
Release files / rockrl-0.4.6.tar.gz
| Download URL | rockrl-0.4.6.tar.gz |
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| Size | 13.1 kB |
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Release files / rockrl-0.4.6-py3-none-any.whl
| Download URL | rockrl-0.4.6-py3-none-any.whl |
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| Size | 18.4 kB |
| Tags | Python 3 |
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