Closed fcharity closed 7 months ago
Thanks! This is a really nice question. First of all, you can start with the famous "The Nuts and Bolts of Deep RL Research" by John Schulman (link). Then personally I'd like to emphasize two things that matter a lot for our specific application autonomous driving: (1) Parallel simulation environment for accelerated experience collection. (2) Logging and visualizing everything you can think of such that later you can debug and reason.
Thank you for your wonderful work! I am very much impressed with the consistency at which the RL training progresses and that must have required some phenomenal hyperparameter tuning and debugging skills. I would like to learn to tune hyperparamters for big and dynamic environments like these. I would appreciate it a lot if you could give me some suggestions and tips for hyperparameter tuning and debugging RL training process. Thank you once again! Cheers!