|
|
from __future__ import annotations
from minigrid.core.constants import COLOR_NAMES from minigrid.core.grid import Grid from minigrid.core.mission import MissionSpace from minigrid.core.world_object import Door from minigrid.minigrid_env import MiniGridEnv
class GoToDoorEnv(MiniGridEnv): """
## Description
This environment is a room with four doors, one on each wall. The agent receives a textual (mission) string as input, telling it which door to go to, (eg: "go to the red door"). It receives a positive reward for performing the `done` action next to the correct door, as indicated in the mission string.
## Mission Space
"go to the {color} door"
{color} is the color of the door. Can be "red", "green", "blue", "purple", "yellow" or "grey".
## 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 | Unused | | 6 | done | Done completing task |
## 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 stands next the correct door performing the `done` action. 2. Timeout (see `max_steps`).
## Registered Configurations
- `MiniGrid-GoToDoor-5x5-v0` - `MiniGrid-GoToDoor-6x6-v0` - `MiniGrid-GoToDoor-8x8-v0`
"""
def __init__(self, size=5, max_steps: int | None = None, **kwargs): assert size >= 5 self.size = size mission_space = MissionSpace( mission_func=self._gen_mission, ordered_placeholders=[COLOR_NAMES], )
if max_steps is None: max_steps = 4 * size**2
super().__init__( mission_space=mission_space, width=size, height=size, # Set this to True for maximum speed see_through_walls=True, max_steps=max_steps, **kwargs, )
@staticmethod def _gen_mission(color: str): return f"go to the {color} door"
def _gen_grid(self, width, height): # Create the grid self.grid = Grid(width, height)
# Randomly vary the room width and height width = self._rand_int(5, width + 1) height = self._rand_int(5, height + 1)
# Generate the surrounding walls self.grid.wall_rect(0, 0, width, height)
# Generate the 4 doors at random positions doorPos = [] doorPos.append((self._rand_int(2, width - 2), 0)) doorPos.append((self._rand_int(2, width - 2), height - 1)) doorPos.append((0, self._rand_int(2, height - 2))) doorPos.append((width - 1, self._rand_int(2, height - 2)))
# Generate the door colors doorColors = [] while len(doorColors) < len(doorPos): color = self._rand_elem(COLOR_NAMES) if color in doorColors: continue doorColors.append(color)
# Place the doors in the grid for idx, pos in enumerate(doorPos): color = doorColors[idx] self.grid.set(*pos, Door(color))
# Randomize the agent start position and orientation self.place_agent(size=(width, height))
# Select a random target door doorIdx = self._rand_int(0, len(doorPos)) self.target_pos = doorPos[doorIdx] self.target_color = doorColors[doorIdx]
# Generate the mission string self.mission = "go to the %s door" % self.target_color
def step(self, action): obs, reward, terminated, truncated, info = super().step(action)
ax, ay = self.agent_pos tx, ty = self.target_pos
# Don't let the agent open any of the doors if action == self.actions.toggle: terminated = True
# Reward performing done action in front of the target door if action == self.actions.done: if (ax == tx and abs(ay - ty) == 1) or (ay == ty and abs(ax - tx) == 1): reward = self._reward() terminated = True
return obs, reward, terminated, truncated, info
|