| ## Multilevel Robot Environment |
|
|
| A simple minigame environment with multiple mini-levels for the robot to pass. |
| For levels that feature coins, all coins must be picked up before proceeding to the next level is possible. |
| The final level features some enemy robots to avoid. |
|
|
| ### Observations: |
| - Current n_steps / reset_after, |
| - Position of the current level's goal in the robot's local reference, |
| - Position of the closest coin in the robot's local reference, |
| - Position of the closest enemy in the robot's local reference, |
| - Movement direction of the closest enemy, |
| - Robot velocity, |
| - Whether all coins for the current level have been collected (0 or 1) |
|
|
| ### Action space: |
| ```gdscript |
| func get_action_space() -> Dictionary: |
| return { |
| "movement" : { |
| "size": 2, |
| "action_type": "continuous" |
| } |
| } |
| ``` |
|
|
| ### Rewards: |
| - Positive reward for picking up a coin, |
| - Negative reward (and episode end) on collision with enemy robot, |
| - Negative reward (and episode end) on robot falling down, |
| - Positive reward (and episode end) on robot reaching the end of the level by passing through the portal at the end of the level, |
| - Positive reward every time the robot gets closer to the portal than the previous minimum distance (min distance is restarted each episode). |
|
|
| ### Game over / episode end conditions: |
| An episode ends if the robot falls, collides with an enemy robot or finishes a level by passing through the portal. |
|
|
| ### Running inference with the pretrained onnx model: |
| After opening the project in Godot, open the training_scene and click on `Run Current Scene` or press `F6` |
| |
| ### Training: |
| The default scene (training_scene) can be used for training. |