OS_deepracerModel

This is an AWS DeepRacer model, trained on AWS Console for the AWS DeepRacer Competition

The reward function is a basic template that can produce results on any track with 3 to 5 hours of training.

//Reward Function def reward_function(params):

if params['all_wheels_on_track']:
    reward = params['progress']
else:
    reward = 0.00001  //some very small value

return float(reward)

Hyperparameters Used

At initial training with above reward function, I trained with default hyperparameters But as the model got better, increasing the number of experience episodes between each policy-updating iteration produced positive results

Action space

The action space of this model Steering angle:: 30 degrees Steering angle granularity:: 5 Max Speed:: 6 m/s Speed graularity:: 3

Results:: after 4 hours of transfer learning anchieved 00:00:22.678 on re:invent 2018 track