This is a fork of the OpenAI Spinning Up in Deep RL repository.

The original repository can be found here

This fork is intended to be an up to date version of the original repository, with the following changes:

1. The code has been updated to be compatible with Python 3.9
2. We only have support for PyTorch and removed support for Tensorflow.
3. We updated readme files and other documentation to be more accessible for beginners.

Installation

To install the package, run the following command in the root directory of the repository:

conda create -n spinningup python=3.9
conda activate spinningup

git clone https://github.com/openai/spinningup.git
cd spinningup
pip install -e .

Welcome to Spinning Up in Deep RL!

This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL).

For the unfamiliar: reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning.

This module contains a variety of helpful resources, including:

• a short introduction to RL terminology, kinds of algorithms, and basic theory,
• an essay about how to grow into an RL research role,
• a curated list of important papers organized by topic,
• a well-documented code repo of short, standalone implementations of key algorithms,
• and a few exercises to serve as warm-ups.

Get started at spinningup.openai.com!

Citing Spinning Up

If you reference or use Spinning Up in your research, please cite:

@article{SpinningUp2018,
    author = {Achiam, Joshua},
    title = {{Spinning Up in Deep Reinforcement Learning}},
    year = {2018}
}