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- from minigrid.core.grid import Grid
- from minigrid.core.mission import MissionSpace
- from minigrid.core.world_object import Goal
- from minigrid.minigrid import MiniGridEnv
- class EmptyEnv(MiniGridEnv):
- """
- ### Description
- This environment is an empty room, and the goal of the agent is to reach the
- green goal square, which provides a sparse reward. A small penalty is
- subtracted for the number of steps to reach the goal. This environment is
- useful, with small rooms, to validate that your RL algorithm works
- correctly, and with large rooms to experiment with sparse rewards and
- exploration. The random variants of the environment have the agent starting
- at a random position for each episode, while the regular variants have the
- agent always starting in the corner opposite to the goal.
- ### Mission Space
- "get to the green goal square"
- ### 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 | 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' 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-Empty-5x5-v0`
- - `MiniGrid-Empty-Random-5x5-v0`
- - `MiniGrid-Empty-6x6-v0`
- - `MiniGrid-Empty-Random-6x6-v0`
- - `MiniGrid-Empty-8x8-v0`
- - `MiniGrid-Empty-16x16-v0`
- """
- def __init__(self, size=8, agent_start_pos=(1, 1), agent_start_dir=0, **kwargs):
- self.agent_start_pos = agent_start_pos
- self.agent_start_dir = agent_start_dir
- mission_space = MissionSpace(
- mission_func=lambda: "get to the green goal square"
- )
- super().__init__(
- mission_space=mission_space,
- grid_size=size,
- max_steps=4 * size * size,
- # Set this to True for maximum speed
- see_through_walls=True,
- **kwargs
- )
- 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 square in the bottom-right corner
- self.put_obj(Goal(), width - 2, height - 2)
- # Place the agent
- if self.agent_start_pos is not None:
- self.agent_pos = self.agent_start_pos
- self.agent_dir = self.agent_start_dir
- else:
- self.place_agent()
- self.mission = "get to the green goal square"
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