polycraft-lab 0.1.0a0

A tool to help train RL agents in novel environments.

Polycraft AI Lab (PAL)

A tool to help train reinforcement learning models to handle novel environments.

About

Polycraft AI Lab consists of a wrapper for Polycraft World game environments. These environments can used to train RL models that respond to novel tasks and scenarios.

Usage

1a. Install via package

First, download Polycraft AI Lab using pip:

pip install polycraft-lab

This downloads the polycraft-lab package from pip, which contains tools to easily set up and manage the Polycraft game client.

To install the most recent changes (experimental version):

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://test.pypi.org/simple/ polycraft-lab

1b. Local Installation

Alternatively, to install the latest version from source:

git clone https://github.com/PolycraftWorld/polycraft-ai-lab
pip install ./polycraft-ai-lab

If you installed PAL using method (1a), this isn't required.

2. Import and Use

Now train your agent like you would do with any other gym-style environment:

from polycraft_lab.envs.helpers import setup_env

env = setup_env('pogo_stick')
observation = env.reset()
for _ in range(1000):
    env.render()
    action = env.action_space.sample() # your agent here (this takes random actions)
    observation, reward, done, info = env.step(action)

    if done:
        observation = env.reset()
env.close()

Polycraft AI Lab also contains a wrapper [WIP] to start experiment creation from the command line. The following begins the experiment creation process by launching Minecraft:

python -m polycraft_lab.ect --create EXPERIMENT_NAME --launch

Running python -m polycraft_lab.ect --create EXPERIMENT_NAME will allow you to create simpler experiments, allowing configuration of more high-level domain attributes, like action space and a preconfigured goal, such as finding diamonds as quickly as possible.

Development

Clone out the repository:

git clone https://github.com/PolycraftWorld/polycraft-ai-lab.git

Optionally, you can create a virtual environment to store dependencies.

In any case, install the dependencies:

pip install -r requirements.txt

Alternatively, a virtual environment can be created with the necessary dependencies by running:

cd polycraft-ai-lab
pipenv install

Distribution

Polycraft AI Lab will be distributed using pip.

The easy way to upload to upload to the test PyPI index:

./release.sh

To release to the live PyPI index:

./release.sh --release