MIT Introduction to Deep Learning 6.S191: Lecture 5
Deep Reinforcement Learning
Lecturer: Alexander Amini
2023 Edition

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Lecture Outline:
0:00 Introduction
3:49 Classes of learning problems
6:48 Definitions
12:24 The Q function
17:06 Deeper into the Q function
21:32 Deep Q Networks
29:15 Atari results and limitations
32:42 Policy learning algorithms
36:42 Discrete vs continuous actions
39:48 Training policy gradients
47:17 RL in real life
49:55 VISTA simulator
52:04 AlphaGo and AlphaZero and MuZero
56:34 Summary


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