The source code and dockerfile for the GSW2024 AI Lab.
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from __future__ import annotations
from minigrid.core.mission import MissionSpace
from minigrid.core.roomgrid import RoomGrid
class UnlockEnv(RoomGrid):
"""
## Description
The agent has to open a locked door. This environment can be solved without
relying on language.
## Mission Space
"open the door"
## 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/minigrid.py](minigrid/minigrid.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 opens the door.
2. Timeout (see `max_steps`).
## Registered Configurations
- `MiniGrid-Unlock-v0`
"""
def __init__(self, max_steps: int | None = None, **kwargs):
room_size = 6
mission_space = MissionSpace(mission_func=self._gen_mission)
if max_steps is None:
max_steps = 8 * room_size**2
super().__init__(
mission_space=mission_space,
num_rows=1,
num_cols=2,
room_size=room_size,
max_steps=max_steps,
**kwargs,
)
@staticmethod
def _gen_mission():
return "open the door"
def _gen_grid(self, width, height):
super()._gen_grid(width, height)
# Make sure the two rooms are directly connected by a locked door
door, _ = self.add_door(0, 0, 0, locked=True)
# Add a key to unlock the door
self.add_object(0, 0, "key", door.color)
self.place_agent(0, 0)
self.door = door
self.mission = "open the door"
def step(self, action):
obs, reward, terminated, truncated, info = super().step(action)
if action == self.actions.toggle:
if self.door.is_open:
reward = self._reward()
terminated = True
return obs, reward, terminated, truncated, info