To install and use ML-Agents, you need install Unity, clone this repository and install Python with additional dependencies. Each of the subsections below overviews each step, in addition to a Docker set-up.
Download and install Unity. If you would like to use our Docker set-up (introduced later), make sure to select the Linux Build Support component when installing Unity.
Once installed, you will want to clone the ML-Agents Toolkit GitHub repository.
git clone https://github.com/Unity-Technologies/ml-agents.git
The unity-environment directory in this repository contains the Unity Assets
to add to your projects. The python directory contains the training code.
Both directories are located at the root of the repository.
In order to use ML-Agents toolkit, you need Python 3.5 or 3.6 along with the dependencies listed in the requirements file. Some of the primary dependencies include:
If you are a Windows user who is new to Python and TensorFlow, follow this guide to set up your Python environment.
Download and install Python 3 if you do not already have it.
If your Python environment doesn't include pip, see these
instructions
on installing it.
To install dependencies, go into the python subdirectory of the repository,
and run from the command line:
pip3 install .
If you'd like to use Docker for ML-Agents, please follow this guide.
The Basic Guide page contains several short tutorials on setting up the ML-Agents toolkit within Unity, running a pre-trained model, in addition to building and training environments.
If you run into any problems regarding ML-Agents, refer to our FAQ and our Limitations pages. If you can't find anything please submit an issue and make sure to cite relevant information on OS, Python version, and exact error message (whenever possible).