You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

86 lines
2.3 KiB

3 months ago
  1. ---
  2. hide-toc: true
  3. firstpage:
  4. lastpage:
  5. ---
  6. ```{project-logo} _static/img/minigrid-text.png
  7. :alt: Minigrid Logo
  8. ```
  9. ```{project-heading}
  10. Minigrid contains simple and easily configurable grid world environments to conduct Reinforcement Learning research. This library was previously known as gym-minigrid.
  11. ```
  12. ```{figure} ../figures/door-key-curriculum.gif
  13. :alt: door key environment gif
  14. :width: 350
  15. :height: 350
  16. ```
  17. This library contains a collection of 2D grid-world environments with goal-oriented tasks. The agent in these environments is a triangle-like agent with a discrete action space. The tasks involve solving different maze maps and interacting with different objects such as doors, keys, or boxes. The design of the library is meant to be simple, fast, and easily customizable.
  18. In addition, the environments found in the [BabyAI](https://github.com/mila-iqia/babyai) repository have been included in Minigrid and will be further maintained under this library.
  19. The Gymnasium interface allows to initialize and interact with the Minigrid default environments as follows:
  20. ```{code-block} python
  21. import gymnasium as gym
  22. env = gym.make("MiniGrid-Empty-5x5-v0", render_mode="human")
  23. observation, info = env.reset(seed=42)
  24. for _ in range(1000):
  25. action = policy(observation) # User-defined policy function
  26. observation, reward, terminated, truncated, info = env.step(action)
  27. if terminated or truncated:
  28. observation, info = env.reset()
  29. env.close()
  30. ```
  31. To cite this project please use:
  32. ```bibtex
  33. @article{MinigridMiniworld23,
  34. author = {Maxime Chevalier-Boisvert and Bolun Dai and Mark Towers and Rodrigo de Lazcano and Lucas Willems and Salem Lahlou and Suman Pal and Pablo Samuel Castro and Jordan Terry},
  35. title = {Minigrid \& Miniworld: Modular \& Customizable Reinforcement Learning Environments for Goal-Oriented Tasks},
  36. journal = {CoRR},
  37. volume = {abs/2306.13831},
  38. year = {2023},
  39. }
  40. ```
  41. ```{toctree}
  42. :hidden:
  43. :caption: Introduction
  44. content/basic_usage
  45. content/publications
  46. content/create_env_tutorial
  47. content/training
  48. ```
  49. ```{toctree}
  50. :hidden:
  51. :caption: Wrappers
  52. api/wrapper
  53. ```
  54. ```{toctree}
  55. :hidden:
  56. :caption: Environments
  57. environments/minigrid/index
  58. environments/babyai/index
  59. ```
  60. ```{toctree}
  61. :hidden:
  62. :caption: Development
  63. release_notes
  64. Github <https://github.com/Farama-Foundation/MiniGrid>
  65. ```