Automated Parking Using RL, a Unity ML-Agents Tutorial.

In this tutorial I will show you, how to use ML-Agents, and create an automated parking system using reinforcement learning.

Intro: 0:00
Requirements: 1:03
Installing Unity / Opening the project: 1:36
Installing ML-Agents (Unity): 2:49
Installing Python / ML-Agents: 4:02
Installing PyTorch: 6:16
Verifying the install: 7:09
Taking a look at the environment: 7:46
Taking a look at the agent's code: 18:29
The hardest part, rewards: 21:17
Preparing the environment for training: 22:26
Creating a demo file: 24:13
Looking at the trainer config: 25:43
Training from the editor: 31:45
Spinning up Tensorboard: 33:23
Training from a build: 35:38
Checking statistics: 38:26
Deploying the model: 39:25

[baselmohamed]

Hey is it a problem that it doesn't show the unity logo in cmd. I followed the same exact steps but that is the only thing not showing.
Thank you btw

[Gaganac-]

i am not able to download unity editors in my computer i tried everything but there is again same issue please help me

[yebv]

That's really a nice project, but I want to know if I want to train this env by other algorithms, how can I do that? Thank you!

[gabrielmaestrecosta]

My computer has a compilation error, is it because I use archlinux?? I can't load the environment, it doesn't show anything on my screen when I load the project

[isolatedsushi]

Awesome video! However what I don't understand is why each agent needs it's own parking lot for parallel parking. Why can't there be multiple cars all trying to park on the same spot if you disable their collisions. Could you explain this?

[irynatyshchenko]

mlagents-learn trainer_settings.yaml --run-id="TutorialRun" --quality-level=0

for logs:
tensorboard --logdir results