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Reinforcement Learning for Minecraft Parkour

Louis Caubet, Firas Ben Jedidia, Long Van Tran Ha, Léo Feliers, Inès Vignal
2023 Project for the INF581 Advanced Machine Learning course at Ecole Polytechnique.

Installation instructions

We recommend using Python 3.9 in a virtual environment to run this project.

git clone https://github.com/LouisCaubet/RLMinecraftParkour.git

cd RLMinecraftParkour
  • Install python dependencies:
pip install -r requirements.txt
  • Install Malmo & MalmoEnv:
git clone https://github.com/Microsoft/malmo.git

cd malmo/Minecraft

(echo -n "malmomod.version=" && cat ../VERSION) > ./src/main/resources/version.properties

Running the code

Start Minecraft with Malmo in a terminal by running

cd malmo/Minecraft
launchClient.bat -port 9000 -env

Open another terminal to run our code.

You can then run the desired Python script. Make sure it is executed from the root of the project.

  • python src/test_parkour_env.py will simply open the parkour_env in Minecraft.
  • python src/sb3_training.py will run the training using Stable-Baselines3
  • python src/sb3_testing.py will run the SB3 trained model in inference mode.

Configuration

Use the .env file for configuration. Here's a list of environment variables we use:

  • MINERL_PARKOUR_MAP: Path to the CSV defining the map.
  • MALMO_PORT: Port on which Malmo is running (default: 9000)
  • SB3_ALGO: Algorithm to use for training. Possible values: DQN, PPO, A2C
  • SB3_TIMESTEPS: Number of training timesteps
  • S3_TRAINED_MODEL_NAME: Name under which to save the model after training.
  • SB3_INFERENCE_MODEL_NAME: Model to use for inference in the sb3_predict script.
  • SB3_INFERENCE_STEPS: Number of steps to run inference for.

Results

Level 1: Straight line, easy first level to test setup

Trained using PPO with 10k steps.

Action space: Move, Strafe

Rewards:

  • +100 for reaching the diamond block
  • +10 for each (gold) block towards the goal
  • -100 and end of episode when touching the bedrock
Level1.mp4

Level 2: Narrower straight line with one-block jump

Action space: Move, Strafe, JumpStrafe

Rewards:

  • +100 for reaching the diamond block
  • +10 for each (gold) block towards the goal
  • -100 and end of episode when touching the bedrock

When training using PPO with 10k timesteps, the agent hacks the game! (Manages to jump for way longer distances that it should be possible)

Level2-hack.mp4

To prevent this, add a minimum delay of 0.1s between actions. To adapt the agent to this new environment, we finetune the previous model for 2k more timesteps. Now, it works!

Level2-success.mp4

Note: Due to the time.sleep, sometimes the +100 reward is not given despite the agent being on the diamond block.