Reinforcement learning

Course summary

• Announcements (Forum)
• Logistics (File)
• Schedule (File)
• Scribe interest form (PhD only) (URL)

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Lecture Notes

• Dynamic Programming (File)
• Linear Programming (File)

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17 February - 23 February

• Lecture 1: Introduction + Dynamic Programming I (File)
• Notebook 1 (Folder)

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24 february - 2 March

• Lecture 2: Dynamic Programming II (File)

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3 March - 9 March

• Lecture 3: Linear Programming (File)

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10 March - 16 March

• Notebook 2 (File)

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17 March - 23 March

• Lecture 4: Policy Gradient methods I (File)

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24 March - 30 March

• Lecture 5: Policy Gradient methods II (File)

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31 March - 6 April

• Lecture 6: Deep Reinforcement Learning (File)
• Notebook 3: Policy Gradient (File)

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7 April - 13 April

• Project List (File)
• Lecture 7: Imitation Learning (File)

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14 April - 20 April

• Cartpole notebook (File)

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21 April - 27 April

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28 April - 4 May

• Lecture 8 (File)
• Supplementary material: Review article on Alignment (File)
• Supplementary slides: Markov Games (File)
• poster template (File)

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12 May - 18 May

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26 May - June 1

• Scribe template (File)

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