dist_shift2.md 1.6 KB
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title: Dist Shift2
Dist Shift2
Description
This environment is based on one of the 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_IDXandCOLOR_TO_IDXmapping can be found in minigrid/minigrid.pySTATErefers 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:
- The agent reaches the goal.
- The agent falls into lava.
- Timeout (see
max_steps).
Registered Configurations
MiniGrid-DistShift1-v0MiniGrid-DistShift2-v0