minerl 0.1.11

MineRL environment and data loader for reinforcement learning from human demonstration in Minecraft

The MineRL Python Package

Python package providing easy to use gym environments and a simple data api for the MineRLv0 dataset.

To get started please read the docs here!

Installation

With JDK-8 installed run this command

pip3 install --upgrade minerl

Basic Usage

Running an environment:

import minerl
import gym
env = gym.make('MineRLNavigateDense-v0')


obs, _ = env.reset()

done = False
while not done:
    action = env.action_space.sample() 
 
    # One can also take a no_op action with
    # action =env.action_space.noop()
    
 
    obs, reward, done, info = env.step(
        action)

Sampling the dataset:

import minerl

# YOU ONLY NEED TO DO THIS ONCE!
minerl.data.download('/your/local/path')

data = minerl.data.make('MineRLObtainDiamond-v0')

# Iterate through a single epoch gathering sequences of at most 32 steps
for obs, rew, done, act in data.seq_iter(num_epochs=1, max_sequence_len=32):
    print("Number of diffrent actions:", len(act))
    for action in act:
        print(act)
    print("Number of diffrent observations:", len(obs), obs)
    for observation in obs:
        print(obs)
    print("Rewards:", rew)
    print("Dones:", done)

MineRL Competition

If you're here for the MineRL competition. Please check the main competition website here.