This repository includes a compilation of reward functions for the AWS Deep Racer service. They have been collected from many other authors with the interest of conducting a comparative study.
All the files include a initial description with:
'''
@author: <Name> // <username>
@Link: https://github.com/<username>/<repo>
@License: <LICENSE If any>
'''The classification system is based solely on the input variables used in the function.
- Void: None of input params
- Single: One input var i.e. all_wheels_on_track
- Double: Two ...
- Tredecuple: All the input
The params dictionary object contains the following key-value pairs:
params = {
"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, # number steps completed
"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.
}- What means v0 & v1? v0 It's about the Deep Racer SDK, some examples uses a
reward_function(param1, param2,...)version with params in a verbose way, but last version (v1) uses the dictionary defined before:reward_function(params). - Which license are you using? Each file includes its licence if available, rest of own work is under MIT license.