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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
MineRL Competition for Sample Efficient Reinforcement Learning - Python Package
| Date | Stars |
|---|---|
| 2026-07-31 | 969 |
| 2026-08-01 | 969 |
| 2026-08-02 | 969 |
| 2026-08-06 | 969 |
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# The [MineRL](http://minerl.io) Python Package
[](https://minerl.readthedocs.io/en/latest/?badge=latest)
[](https://pepy.tech/project/minerl)
[](https://badge.fury.io/py/minerl)
[](https://github.com/minerllabs/minerl/issues)
[](https://github.com/minerllabs/minerl/issues?utf8=%E2%9C%93&q=is%3Aissue+is%3Aopen+label%3Abug)
[](https://discord.gg/BT9uegr)
Python package providing easy to use Gym environments and data access for training agents in Minecraft.
Curious to see what people have done with MineRL? See [this page where we collect projects using MineRL](https://minerl.readthedocs.io/en/latest/notes/useful-links.html). **Got a project using MineRL (academic or fun hobby project)?** Edit [this file](https://github.com/minerllabs/minerl/blob/dev/docs/source/notes/useful-links.rst), add links to your projects and create a PR!
To get started with MineRL, [check out the docs here](https://minerl.readthedocs.io/en/latest/)!
## ⚠️Update regarding MineRL-v0 data on 17th June 2024
The original data mirrors for MineRL-v0 are down (e.g., original `MineRLObtainDiamond-v0` data). We have uploaded copies of the primary datasets to this Zenodo record so people can find them: https://zenodo.org/records/12659939
## MineRL Versions
MineRL consists of three unique versions, each with a slightly different sets of features. See full comparison [here](https://minerl.readthedocs.io/en/v1.0.0/notes/versions.html).
* v1.0: [[Code](https://github.com/minerllabs/minerl)][[Docs](https://minerl.readthedocs.io/en/latest/)]
This version you are looking at. Needed for the [OpenAI VPT](https://github.com/openai/Video-Pre-Training) models and the [MineRL BASALT 2022](https://www.aicrowd.com/challenges/neurips-2022-minerl-basalt-competition) competition.
* v0.4: [[Code](https://github.com/minerllabs/minerl/tree/v0.4)][[Docs](https://minerl.readthedocs.io/en/v0.4.4/)]
Version used in the 2021 competitions (Diamond and BASALT). Supports the original [MineRL-v0 dataset](https://arxiv.org/abs/1907.13440). Install with `pip install minerl==0.4.4`
* v0.3: [[Code](https://github.com/minerllabs/minerl/tree/pypi_0.3.7)][[Docs](https://minerl.readthedocs.io/en/v0.3.7/)]
Version used prior to 2021, including the first two MineRL competitions (2019 and 2020). Supports the original [MineRL-v0 dataset](https://arxiv.org/abs/1907.13440). Install with `pip install minerl==0.3.7`
## Installation
Install [requirements](https://minerl.readthedocs.io/en/latest/tutorials/index.html) (Java JDK 8 is **required**. Mac may require [additional steps](https://github.com/minerllabs/minerl/issues/659#issuecomment-1306635414)) and then install MineRL with
```
pip install git+https://github.com/minerllabs/minerl
```
## Basic Usage
Can be used much like any Gym environment:
```python
import gym
import minerl
# Uncomment to see more logs of the MineRL launch
# import coloredlogs
# coloredlogs.install(logging.DEBUG)
env = gym.make("MineRLBasaltBuildVillageHouse-v0")
obs = env.reset()
done = False
while not done:
ac = env.action_space.noop()
# Spin around to see what is around us
ac["camera"] = [0, 3]
obs, reward, done, info = env.step(ac)
env.render()
env.close()
```
Check the [documentation](https://minerl.readthedocs.io/en/latest) for further examples and notes.
## Major changes in v1.0
- New Minecraft version (11.2 -> 16.5)
- Larger resolution by default (64x64 -> 640x360)
- Near-human action-space: no more `craft` and `smelt` actions. Only GUI and mouse contExcerpt of 4,118 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a3516c1cd08928ba, desc:reinforcement learning