Crafter

Open world survival environment for reinforcement learning.

Highlights

Crafter is a procedurally generated 2D world, where the agent finds food, avoids or defends against zombies, and collect materials to build tools, which in turn unlock new materials.

• Generalization: New procedurally generated map for each episode.
• Exploration: Materials unlock new tools which unlock new materials.
• Memory: Input images show small part of the world centered at the agent.
• No trivial behaviors: Must find food and avoid or defend against zombies.
• Easy: Flat categorical action space with 12 actions.
• Fast: Runs at 2000 FPS on a simple laptop.
• Reproducible: All randomness is controlled by a seed.

Play Yourself

You can play the game yourself with an interactive window and keyboard input. The mapping from keys to actions, health level, and inventory state are printed to the terminal.

# Install with GUI
pip3 install 'crafter[gui]'

# Start the game
crafter

# Alternative way to start the game
python3 -m crafter.run_gui

The following optional command line flags are available:

Training Agents

Installation: pip3 install -U crafter

The environment follows the OpenAI Gym interface:

import crafter

env = crafter.Env(seed=0)
obs = env.reset()
assert obs['image'].shape == (64, 64, 3)

done = False
while not done:
  action = env.action_space.sample()
  obs, reward, done, info = env.step(action)

Environment Details

Constructor

For comparability between papers, we recommend using the environment in its default configuration. Nonetheless, the environment can be configured via its constructor:

crafter.Env(area=(64, 64), view=4, size=64, length=10000, seed=None)

Reward

The reward is sparse. It can either be given to the agent or used as a proxy metric for evaluating unsupervised agents. The reward is 1 when the agent unlocks a new achievement and 0 for all other time steps. The list of achievements is as follows:

• find_food
• defeat_zombie
• collect_wood
• place_table
• make_wood_pickaxe
• collect_stone
• place_stone
• make_stone_pickaxe
• collect_coal
• collect_iron
• place_furnace
• make_iron_pickaxe
• collect_diamond

The set of unlocked achievements can also be accessed via the info dictionary.

Termination

The episode terminates when the health points of the agent reach zero. Episodes also end when reaching a time limit, which is 100,000 steps by default.

Observation Space

Each observation is a dictionary that contains a local image centered at the agent and counters for player health and inventory. The following keys are available:

Action Space

The action space is categorical. Each action is an integer index representing one of the 12 possible actions:

Questions

Please open an issue on Github.