MyMiniGrid

MiniGrid

• The MiniGrid repo: https://github.com/Farama-Foundation/Minigrid
• The MiniGrid document: https://minigrid.farama.org/

Environment Overview

Observations

The observation returned is a dict by default, which commonly contains the following keys:

• image: the main observation, there are three kinds:
  • RGB image: (tile_size*width, tile_size*height, 3)
  • A 3-dimensional ndarray (width, height, 3) where the last dimension contains (OBJECT_IDX, COLOR_IDX, STATE)

    OBJECT_TO_IDX = {"unseen": 0, "empty": 1, "wall": 2, "floor": 3, "door": 4, "key": 5, "ball": 6, "box": 7, "goal": 8, "lava": 9, "agent": 10}
    COLOR_TO_IDX = {"red": 0, "green": 1, "blue": 2, "purple": 3, "yellow": 4, "grey": 5}
    STATE_TO_IDX = {"open": 0, "closed": 1, "locked": 2}

  • Symbolic state representation: a triple of (X, Y, IDX), where X and Y are the coordinates on the grid, and IDX is the id of the object.
• direction: the direction of the agent, Discrete(4).
• mission: the string that indicates the current mission/goal for the agent to complete.

Actions

Original actions:

Num	Name	Action
0	left	Turn left
1	right	Turn right
2	forward	Move forward
3	pickup	Pick up an object
4	drop	Drop an object
5	toggle	Toggle/activate an object
6	done	Done completing task

Wrappers

MiniGrid Wrappers

from minigrid.wrappers import *

• FullyObsWrapper(env): Fully observable gridworld instead of the agent view
• RGBImgObsWrapper(env, tile_size=8): use fully observable RGB image as observation
• ImgObsWrapper(env): Get rid of the 'mission' field
• RGBImgPartialObsWrapper(env, tile_size=8): use partially observable RGB image as observation
• SymbolicObsWrapper(env): fully observable grid with a symbolic state representation
• ViewSizeWrapper(env,agent_view_size=7): set the view size of the agent

The full reference of wrappers: https://minigrid.farama.org/api/wrappers/

Self-Defined Wrappers

from RLEnvs.MyMiniGrid.Wrappers import *

• AgentLocation: The wrapper to indicate the location of the agent in the info.
• MovetoFourDirectionsWrapper: Modify the action space to Discrete(4), making the agent only moves to four directions for one step:
  • 0 - move forward
  • 1 - move to left
  • 2 - move to right
  • 3 - move backward

Reference

@article{MinigridMiniworld23,
  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},
  title        = {Minigrid \& Miniworld: Modular \& Customizable Reinforcement Learning Environments for Goal-Oriented Tasks},
  journal      = {CoRR},
  volume       = {abs/2306.13831},
  year         = {2023},
}