https://github.com/kartik2309/rlpack
Implementation of RL Algorithms with PyTorch.
https://github.com/kartik2309/rlpack
a2c-agent a2c-algorithm a2c-pytorch a3c a3c-agent a3c-pytorch deep-reinforcement-learning dqn dqn-pytorch gym-environments prioritized-experience-replay pytorch-implementation reinforcement-learning
Last synced: about 2 months ago
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Implementation of RL Algorithms with PyTorch.
- Host: GitHub
- URL: https://github.com/kartik2309/rlpack
- Owner: kartik2309
- License: mit
- Created: 2022-08-21T22:03:38.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2023-01-16T19:06:35.000Z (almost 3 years ago)
- Last Synced: 2025-09-13T23:51:22.558Z (2 months ago)
- Topics: a2c-agent, a2c-algorithm, a2c-pytorch, a3c, a3c-agent, a3c-pytorch, deep-reinforcement-learning, dqn, dqn-pytorch, gym-environments, prioritized-experience-replay, pytorch-implementation, reinforcement-learning
- Language: Python
- Homepage:
- Size: 9.66 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
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README
# RLPack
# Introduction
RLPack; Reinforcement Learning Package is the implementation of RL Algorithms built on top of PyTorch. Heavy
workloads have been optimized with C++ backend with CUDA and OpenMP (depending on the hardware availability).
# Installation
#### To install RLPack, you can simply do
```bash
python -m pip install -U pip
pip install RLPack
```
#### To build and install RLPack from source, simply clone and install as follows:
```bash
python -m pip install -U pip
git clone https://github.com/kartik2309/RLPack.git
cd RLPack
pip install . --use-feature=in-tree-build
```
This will install the package in your python environment.
# Documentation
RLPack documentation was generated by Doxygen. It can be referred [here](https://kartik2309.github.io/RLPack/html/index.html)
# Issues and bugs
Please raise an issue if you encounter a bug. If you would like to fix the bug and contribute to RLPack, kindly refer
to [CONTRIBUTING.md](https://github.com/kartik2309/RLPack/blob/master/CONTRIBUTING.md)
# License
RLPack is released under [MIT LICENSE](https://github.com/kartik2309/RLPack/blob/master/LICENSE.md).