A simple implementation of the environment in Google Deepmind's paper "Relational Deep Reinforcement Learning". No rendering, only for computer training and testing.
kwargs of gym.make
| metadata | description | default |
|---|---|---|
| max_length | the number of boxes in the path to the goal | 4 |
| max_branch_num | the number of distractor branches | 4 |
| branch_length | the length of the distractor branches | 1 |
Type: ndarray(14, 14, 3)
| Max | Min |
|---|---|
| 0.0 | 255.0 |
| Type | Color |
|---|---|
| Wall | RGB(0.0, 0.0, 0.0) |
| Space | RGB(192.25, 191.25, 191.25) |
| Agent | RGB(127.5, 127.5, 127.5) |
| Gem | RGB(255.0, 255.0, 255.0) |
Type: Discrete(4)
| Num | Action |
|---|---|
| 0 | Agent move up |
| 1 | Agent move left |
| 2 | Agent move down |
| 3 | Agent move right |
| action | reward |
|---|---|
| collecting the gem | 10 |
| opening a box in the solution path | 1 |
| opening a distractor box | -1 |
| otherwise | 0 |
Terminated when:
- the gem is collected
- a distractor box is opened