Rating is available when the video has been rented.
This feature is not available right now. Please try again later.
Streamed live on Jan 26, 2020
Useful timestamps: 0:24 Video Goal 0:50 Initial Q-Learning Explanation 7:30 Coding starts 35:10 Q&A 46:00 Agent can randomly solve maze 1:00:00 Agent scoring implemented 1:07:00 Setting up 3D visualizer 1:32:00 Detailed discussion of Q matrix, setting things up 1:52:00 Starting to set up QLearning class 2:16:00 Debugging issue in Q matrix update 2:46:00 Setting up larger mazes 3:01:11 Setting up explore vs exploit tradeoff 3:16:00 End of coding, Audience Questions and Discussion
In this recorded live stream I solve a basic reinforcement learning example, what you might consider a hello world for RL. Specifically I set up and solve an arbitrary maze using the Q Learning algorithm. The example is coded in Python and is done from scratch. I know the video is long but everything is covered at a basic level and should be very accessible.