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0:00

Intro

2:32

Classes of Learning Problems

5:35

Reinforcement Learning (RL): Key Concepts

11:41

Defining the Q-function

13:40

How to take actions given a Q-function?

15:35

Deep Reinforcement Learning Algorithms

17:13

Digging deeper into the Q-function

28:30

Downsides of Q-learning

30:32

Policy Gradient (PG): Key Idea

32:42

Policy Gradient (PG): Training

36:30

The Game of Go

38:05

AlphaGo Beats Top Human Player at Go (2016)

41:51

AlphaZero: RL from Self-Play (2018)

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MIT Introduction to Deep Learning 6.S191: Lecture 5 Deep Reinforcement Learning Lecturer: Alexander Amini January 2019 For all lectures, slides and lab materials: http://introtodeeplearning.com/

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