MIT: Deep Reinforcement Learning

MIT: Deep Reinforcement Learning

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Intro

1 of 13

1 of 13

Intro

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MIT: Deep Reinforcement Learning

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  1. 1 Intro
  2. 2 Classes of Learning Problems
  3. 3 Reinforcement Learning (RL): Key Concepts
  4. 4 Defining the Q-function
  5. 5 How to take actions given a Q-function?
  6. 6 Deep Reinforcement Learning Algorithms
  7. 7 Digging deeper into the Q-function
  8. 8 Downsides of Q-learning
  9. 9 Policy Gradient (PG): Key Idea
  10. 10 Policy Gradient (PG): Training
  11. 11 The Game of Go
  12. 12 AlphaGo Beats Top Human Player at Go (2016)
  13. 13 AlphaZero: RL from Self-Play (2018)

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