Multi Room

Action Space	Discrete(7)
Observation Space	Dict('direction': Discrete(4), 'image': Box(0, 255, (7, 7, 3), uint8), 'mission': MissionSpace(<function MultiRoomEnv._gen_mission at 0x7f813f48e8b0>, None))
Reward Range	(0, 1)
Creation	gymnasium.make("MiniGrid-MultiRoom-N6-v0")

Description

This environment has a series of connected rooms with doors that must be opened in order to get to the next room. The final room has the green goal square the agent must get to. This environment is extremely difficult to solve using RL alone. However, by gradually increasing the number of rooms and building a curriculum, the environment can be solved.

Mission Space

“traverse the rooms to get to the goal”

Action Space

Num	Name	Action
0	left	Turn left
1	right	Turn right
2	forward	Move forward
3	pickup	Unused
4	drop	Unused
5	toggle	Toggle/activate an object
6	done	Unused

Observation Encoding

• Each tile is encoded as a 3 dimensional tuple: (OBJECT_IDX, COLOR_IDX, STATE)

• OBJECT_TO_IDX and COLOR_TO_IDX mapping can be found in minigrid/core/constants.py

• STATE refers to the door state with 0=open, 1=closed and 2=locked

Rewards

A reward of ‘1 - 0.9 * (step_count / max_steps)’ is given for success, and ‘0’ for failure.

Termination

The episode ends if any one of the following conditions is met:

1. The agent reaches the goal.

2. Timeout (see max_steps).

Registered Configurations

S: size of map SxS. N: number of rooms.

• MiniGrid-MultiRoom-N2-S4-v0 (two small rooms)

• MiniGrid-MultiRoom-N4-S5-v0 (four rooms)

• MiniGrid-MultiRoom-N6-v0 (six rooms)