AWS DeepRacer Experimentation.
Definition from AWS
The reward function describes immediate feedback (as a score for reward or penalty) when the vehicle takes an action to move from a given position on the track to a new position. Its purpose is to encourage the vehicle to make moves along the track to reach its destination quickly. The model training process will attempt to find a policy which maximizes the average total reward the vehicle experiences.
def reward_function(params) :
reward = ...
return float(reward)
| Name | Description |
|---|---|
| all_wheels_on_track | (boolean) flag to indicate if the vehicle is on the track |
| x | (float) vehicle's x-coordinate in meters |
| y | (float) vehicle's y-coordinate in meters |
| distance_from_center | (float) distance in meters from the track center |
| is_left_of_center | (boolean) flag to indicate if the vehicle is on the left side to the track center or not |
| heading | (float) vehicle's yaw in degrees |
| progress | (float) percentage of track completed |
| steps | (int) numbers of steps completed |
| steering | (float) -1 to 1 (-1 is right, 1 is left) |
| speed | (float) vehicle's speed in meters per second (m/s) |
| steering_angle | (float) vehicle's steering angle in degrees |
| track_width | (float) width of the track |
| waypoints | [[float, float] … ] list of [x,y] as milestones along the track center |
| closest_waypoints | [int, int] indices of the two nearest waypoints |
A copy-and-paste from Amazon AWS of the sample reward function; used for learning purpose.
A first attempt to build a "punisher" reward function to train my model.
Top ten classified in AWS Deepracer leage, in Turin.
An attempt to build an easiest reward function to train my model.
A total failure.
Get last 10000 simulation jobs logs:
aws logs get-log-events --log-group-name "/aws/robomaker/SimulationJobs" --log-stream-name "<STREAM_NAME>" --output text --region us-east-1 > deepracer-sim.log
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