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.
Install Unity 2017.4 or Later
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.
Clone the ML-Agents Toolkit Repository
Once installed, you will want to clone the ML-Agents Toolkit GitHub repository.
git clone https://github.com/Unity-Technologies/ml-agents.git
UnitySDK subdirectory contains the Unity Assets to add to your projects.
It also contains many example environments
that can be used to help get you familiar with Unity.
ml-agents subdirectory contains Python packages which provide
trainers and a Python API to interface with Unity.
gym-unity subdirectory contains a package to interface with OpenAI Gym.
Install Python and mlagents Package
In order to use ML-Agents toolkit, you need Python 3.6 along with the dependencies listed in the requirements file. Some of the primary dependencies include:
- We do not currently support Python 3.7 or Python 3.5.
- If you are using Anaconda and are having trouble with TensorFlow, please see the following note on how to install TensorFlow in an Anaconda environment.
If you are a Windows user who is new to Python and TensorFlow, follow this guide to set up your Python environment.
Mac and Unix Users
Download and install Python 3.6 if you do not already have it.
If your Python environment doesn't include
pip3, see these
on installing it.
To install the dependencies and
mlagents Python package, enter the
ml-agents/ subdirectory and run from the command line:
pip3 install .
If you installed this correctly, you should be able to run
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).