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
Github: github.com/VanIseghemThomas/A...
My website: www.thomasvaniseghem.be/portf...
Proximal Policy Optimisation: openai.com/blog/openai-baseli...
26 июл 2024