To get ML-Agents working with Windows, you will need to have Windows 10 installed. While it is possible for ML-Agents to work on other versions of Windows, we have only tested with a local installation of Windows 10 (not using VM like Bootcamp or Parallels)
We have provided a step by step guide to getting ML-Agents working on Windows.
In oreder to get ML-Agents working with Windows, you will need to have Windows 10 installed. While it is possible for ML-Agents to work on other versions of Windows, we have only tested with a local installation of Windows 10 (not using VM like Bootcamp or Parallels).
Additionally, you will need to check if your GPU is CUDA compatible. Please check Nvidia's page [here](https://developer.nvidia.com/cuda-gpus).
## Step 1: Install Nvidia CUDA toolkit
<ahref="https://developer.nvidia.com/cuda-toolkit-archive"target="_blank">Download</a> and install the CUDA toolkit from Nvidia's archive. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler and a runtime library and is needed to run ML-Agents. You can select the latest or previous releases. In this guide, we are using version 9.1.85.3 ([direct link](https://developer.nvidia.com/compute/cuda/9.1/Prod/patches/3/cuda_9.1.85.3_windows)).
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Once you've signed up, go back to the cuDNN <ahref="https://developer.nvidia.com/cudnn"target="_blank">downloads page</a>. You may or may not be asked to fill out a short survey. When you get to the list cuDNN releases, __make sure you are downloading the right version for the CUDA toolkit you installed in Step 1.__ In this guide, we are using version 7.1.1 for CUDA toolkit version 9.1+ ([direct link](https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.1.1/prod/9.1_20180214/cudnn-9.1-windows10-x64-v7.1)).
## Step 3: Install Python via Anaconda
<ahref="https://www.anaconda.com/download/#windows"target="_blank">Download</a> and install Anaconda for Windows. By using Anaconda, we can use manage seperate enviornments for different distributions of Python. We **strongly** recommend using Python 3 as we do not guarantee supporting Python 2 in future releases. In this guide, we are using Python version 3.6 and Anaconda version 5.1 ([64-bit](https://repo.continuum.io/archive/Anaconda3-5.1.0-Windows-x86_64.exe) or [32-bit](https://repo.continuum.io/archive/Anaconda3-5.1.0-Windows-x86.exe) direct links).
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