# Interesting Environments to try

Here we provide a list of interesting environments you can try to train your agents on:

## MineRL

<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit12/minerl.jpg" alt="MineRL"/>


MineRL is a Python library that provides a Gym interface for interacting with the video game Minecraft, accompanied by datasets of human gameplay.
Every year there are challenges with this library. Check the [website](https://minerl.io/)

To start using this environment, check these resources:
- [What is MineRL?](https://www.youtube.com/watch?v=z6PTrGifupU)
- [First steps in MineRL](https://www.youtube.com/watch?v=8yIrWcyWGek)
- [MineRL documentation and tutorials](https://minerl.readthedocs.io/en/latest/)

## DonkeyCar Simulator

<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit12/donkeycar.jpg" alt="Donkey Car"/>
Donkey is a Self Driving Car Platform for hobby remote control cars.
This simulator version is built on the Unity game platform. It uses their internal physics and graphics and connects to a donkey Python process to use our trained model to control the simulated Donkey (car).


To start using this environment, check these resources:
- [DonkeyCar Simulator documentation](https://docs.donkeycar.com/guide/deep_learning/simulator/)
- [Learn to Drive Smoothly (Antonin Raffin's tutorial) Part 1](https://www.youtube.com/watch?v=ngK33h00iBE)
- [Learn to Drive Smoothly (Antonin Raffin's tutorial) Part 2](https://www.youtube.com/watch?v=DUqssFvcSOY)
- [Learn to Drive Smoothly (Antonin Raffin's tutorial) Part 3](https://www.youtube.com/watch?v=v8j2bpcE4Rg)

- Pretrained agents:
  - https://huggingface.co/araffin/tqc-donkey-mountain-track-v0
  - https://huggingface.co/araffin/tqc-donkey-avc-sparkfun-v0
  - https://huggingface.co/araffin/tqc-donkey-minimonaco-track-v0


## Starcraft II

<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit12/alphastar.jpg" alt="Alphastar"/>

Starcraft II is a famous *real-time strategy game*. DeepMind has used this game for their Deep Reinforcement Learning research with [Alphastar](https://www.deepmind.com/blog/alphastar-mastering-the-real-time-strategy-game-starcraft-ii)

To start using this environment, check these resources:
- [Starcraft gym](http://starcraftgym.com/)
- [A. I. Learns to Play Starcraft 2 (Reinforcement Learning) tutorial](https://www.youtube.com/watch?v=q59wap1ELQ4)

## Author

This section was written by <a href="https://twitter.com/ThomasSimonini"> Thomas Simonini</a>
