Malmö

Project Malmö is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment.

Getting Started

MalmoEnv

MalmoEnv implements an Open AI "gym"-like environment in Python without any native code (communicating directly with Java Minecraft). If you only need this functionallity then please see MalmoEnv. This will most likely be the preferred way to develop with Malmo Minecraft going forward.

If you wish to use the "native" Malmo implementation, either install the "Malmo native Python wheel" (if available for your platform) or a pre-built binary release (more on these options below). Building Malmo yourself from source is always an option!

Advantages:

1. No native code - you don't have to build or install platform dependent code.
2. A single network connection is used to run missions. No dynamic ports means it's more virtualization friendly.
3. A simpler multi-agent coordination protocol. One Minecraft client instance, one single port is used to start missions.
4. Less impedance miss-match with the gym api.

Disadvantages:

1. The existing Malmo examples are not supported (as API used is different). Marlo envs should work with this port.
2. The API is more limited (e.g. selecting video options) - can edit mission xml directly.

Malmo as a native Python wheel

On common Windows, MacOSX and Linux variants it is possible to use pip3 install malmo to install Malmo as a python with native code package: Pip install for Malmo. Once installed, the malmo Python module can be used to download source and examples and start up Minecraft with the Malmo game mod.

Alternatively, a pre-built version of Malmo can be installed as follows:

1. Download the latest pre-built version, for Windows, Linux or MacOSX.
   NOTE: This is not the same as downloading a zip of the source from Github. Doing this will not work unless you are planning to build the source code yourself (which is a lengthier process). If you get errors along the lines of "ImportError: No module named MalmoPython" it will probably be because you have made this mistake.

2. Install the dependencies for your OS: Windows, Linux, MacOSX.

3. Launch Minecraft with our Mod installed. Instructions below.

4. Launch one of our sample agents, as Python, C#, C++ or Java. Instructions below.

5. Follow the Tutorial

6. Explore the Documentation. This is also available in the readme.html in the release zip.

7. Read the Blog for more information.

If you want to build from source then see the build instructions for your OS: Windows, Linux, MacOSX.

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Problems:

We're building up a Troubleshooting page of the wiki for frequently encountered situations. If that doesn't work then please ask a question on our chat page or open a new issue.

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Launching Minecraft with our Mod:

Minecraft needs to create windows and render to them with OpenGL, so the machine you do this from must have a desktop environment.

Go to the folder where you unzipped the release, then:

cd Minecraft
launchClient (On Windows)
./launchClient.sh (On Linux or MacOSX)

or, e.g. launchClient -port 10001 to launch Minecraft on a specific port.

on Linux or MacOSX: ./launchClient.sh -port 10001

NB: If you run this from a terminal, the bottom line will say something like "Building 95%" - ignore this - don't wait for 100%! As long as a Minecraft game window has opened and is displaying the main menu, you are good to go.

By default the Mod chooses port 10000 if available, and will search upwards for a free port if not, up to 11000. The port chosen is shown in the Mod config page.

To change the port while the Mod is running, use the portOverride setting in the Mod config page.

The Mod and the agents use other ports internally, and will find free ones in the range 10000-11000 so if administering a machine for network use these TCP ports should be open.

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Launch an agent:

Running a Python agent:

cd Python_Examples
python3 run_mission.py

Running a C++ agent:

cd Cpp_Examples

To run the pre-built sample:

run_mission (on Windows)
./run_mission (on Linux or MacOSX)

To build the sample yourself:

cmake .
cmake --build .
./run_mission (on Linux or MacOSX)
Debug\run_mission.exe (on Windows)

Running a C# agent:

To run the pre-built sample (on Windows):

cd CSharp_Examples
CSharpExamples_RunMission.exe

To build the sample yourself, open CSharp_Examples/RunMission.csproj in Visual Studio.

Or from the command-line:

cd CSharp_Examples

Then, on Windows:

msbuild RunMission.csproj /p:Platform=x64
bin\x64\Debug\CSharpExamples_RunMission.exe

Running a Java agent:

cd Java_Examples
java -cp MalmoJavaJar.jar:JavaExamples_run_mission.jar -Djava.library.path=. JavaExamples_run_mission (on Linux or MacOSX)
java -cp MalmoJavaJar.jar;JavaExamples_run_mission.jar -Djava.library.path=. JavaExamples_run_mission (on Windows)

Running an Atari agent: (Linux only)

cd Python_Examples
python3 ALE_HAC.py

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Citations

Please cite Malmo as:

Johnson M., Hofmann K., Hutton T., Bignell D. (2016) The Malmo Platform for Artificial Intelligence Experimentation. Proc. 25th International Joint Conference on Artificial Intelligence, Ed. Kambhampati S., p. 4246. AAAI Press, Palo Alto, California USA. https://github.com/Microsoft/malmo

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Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.