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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:
- ca-certificates
- certifi
- cloudpickle
- ffmpeg
- openssl
- pyglet
- python_abi
Setup
Anaconda Environment
C:\Users\username>conda install -c conda-forge gymOpenAI 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
