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