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.
100 lines
3.3 KiB
100 lines
3.3 KiB
from __future__ import annotations
|
|
|
|
from minigrid.core.grid import Grid
|
|
from minigrid.core.mission import MissionSpace
|
|
from minigrid.core.world_object import Door, Goal, Key
|
|
from minigrid.minigrid_env import MiniGridEnv
|
|
|
|
|
|
class SingleDoorEnv(MiniGridEnv):
|
|
|
|
"""
|
|
## Description
|
|
|
|
This environment has a key that the agent must pick up in order to unlock a
|
|
goal and then get to the green goal square. This environment is difficult,
|
|
because of the sparse reward, to solve using classical RL algorithms. It is
|
|
useful to experiment with curiosity or curriculum learning.
|
|
|
|
## Mission Space
|
|
|
|
"use the key to open the door and then get to the goal"
|
|
|
|
## Action Space
|
|
|
|
| Num | Name | Action |
|
|
|-----|--------------|---------------------------|
|
|
| 0 | left | Turn left |
|
|
| 1 | right | Turn right |
|
|
| 2 | forward | Move forward |
|
|
| 3 | pickup | Pick up an object |
|
|
| 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 reaches the goal.
|
|
2. Timeout (see `max_steps`).
|
|
|
|
## Registered Configurations
|
|
|
|
- `MiniGrid-SingleDoor-7x6-v0`
|
|
|
|
|
|
"""
|
|
|
|
def __init__(self, width=7, height=6, max_steps: int | None = None, **kwargs):
|
|
if max_steps is None:
|
|
max_steps = 10 * (width * height)
|
|
mission_space = MissionSpace(mission_func=self._gen_mission)
|
|
super().__init__(
|
|
mission_space=mission_space, width=width, height=height, max_steps=max_steps, **kwargs
|
|
)
|
|
|
|
@staticmethod
|
|
def _gen_mission():
|
|
return "use the key to open the door and then get to the goal"
|
|
|
|
def _gen_grid(self, width, height):
|
|
# Create an empty grid
|
|
self.grid = Grid(width, height)
|
|
|
|
# Generate the surrounding walls
|
|
self.grid.wall_rect(0, 0, width, height)
|
|
|
|
# Place a goal in the bottom-right corner
|
|
self.put_obj(Goal(), width - 2, height - 2)
|
|
|
|
# Create first vertical splitting wall
|
|
# splitIdx = self._rand_int(2, width - 2)
|
|
splitIdxOne = width // 2
|
|
self.grid.vert_wall(splitIdxOne, 0)
|
|
|
|
# Place the agent at a random position and orientation
|
|
# on the left side of the splitting wall
|
|
self.place_agent(size=(splitIdxOne, height))
|
|
|
|
# Place a door in the wall
|
|
doorIdx = height // 2
|
|
self.put_obj(Door("yellow", is_locked=True), splitIdxOne, doorIdx)
|
|
|
|
self.place_obj(obj=Key("yellow"), top=(0, 0), size=(splitIdxOne, height))
|
|
|
|
# Place a yellow key on the left side
|
|
|
|
self.mission = "use the key to open the door and then get to the goal"
|