Welcome to MineRL! This guide will get you started.

To start using the data and set of reinforcement learning environments comprising MineRL, you’ll need to install the main python package, minerl.

  1. First make sure you have JDK 1.8 installed on your system.

    1. Windows installer – On windows go this link and follow the instructions to install JDK 8.

    2. On Mac, you can install java8 using homebrew and AdoptOpenJDK (an open source mirror, used here to get around the fact that Java8 binaries are no longer available directly from Oracle):

      brew tap AdoptOpenJDK/openjdk
      brew cask install adoptopenjdk8
    3. On Debian based systems (Ubuntu!) you can run the following:

      sudo add-apt-repository ppa:openjdk-r/ppa
      sudo apt-get update
      sudo apt-get install openjdk-8-jdk
  2. Now install the minerl package!:

    pip3 install --upgrade minerl


depending on your system you may need the user flag: pip3 install --upgrade minerl --user to install property

  1. (Optional) Download the dataset ~ 60 GB:

    import minerl"/your/local/path/")

    Or simply download a single experiment'/your/local/path',experiment='MineRLObtainDiamondVectorObf-v0')

    For a complete list of published experiments, checkout the environment documentation. If you are here for the MineRL competition, checkout the competition environments.

That’s it! Now you’re good to go :) 💯💯💯


Currently minerl only supports environment rendering in headed environments (machines with monitors attached).

In order to run minerl environments without a head use a software renderer such as xvfb:

xvfb-run python3 <>