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AUTOGENERATED: DO NOT EDIT FILE DIRECTLY
title: Dist Shift2
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# Dist Shift2

### Description

This environment is based on one of the DeepMind [AI safety gridworlds]
(https://github.com/deepmind/ai-safety-gridworlds). The agent starts in the
top-left corner and must reach the goal which is in the top-right corner,
but has to avoid stepping into lava on its way. The aim of this environment
is to test an agent's ability to generalize. There are two slightly
different variants of the environment, so that the agent can be trained on
one variant and tested on the other.

### 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. The agent falls into lava.
3. Timeout (see `max_steps`).

### Registered Configurations

- `MiniGrid-DistShift1-v0`
- `MiniGrid-DistShift2-v0`