Components

Library

Accessible via pip.

Service

Site and API for comparing algorithm performance.

Supporting Libraries / Dependencies

The install of this library also includes installation of the following supporting libraries installed either via conda pip or through the Anaconda distribution.

Required Libraries:

Setup

Anaconda Environment

C:\Users\username>conda install -c conda-forge gym

OpenAI Gym in Google Colab

Google Colaboratory

colab.research.google.com

Resources

Documentation

Gym: A toolkit for developing and comparing reinforcement learning algorithms

The gym library is a collection of test problems - environments - that you can use to work out your reinforcement learning algorithms. These environments have a shared interface, allowing you to write general algorithms. To get started, you'll need to have Python 3.5+ installed. Simply install gym using pip: And you're good to go!

gym.openai.com

Environments

Gym: A toolkit for developing and comparing reinforcement learning algorithms

A toolkit for developing and comparing reinforcement learning algorithms

gym.openai.com