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UC Berkeley CS 285: Deep Reinforcement Learning →0/11
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CS 285: Lecture 1, Introduction. Part 2

17:54
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CS 285: Lecture 1, Introduction. Part 3

29:01
3

CS 285: Lecture 2, Imitation Learning. Part 1

24:47
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CS 285: Lecture 2, Imitation Learning. Part 2

23:06
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CS 285: Lecture 2, Imitation Learning. Part 3

32:23
6

CS 285: Lecture 4, Part 1

26:28
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Lecture 5, Part 1 (CS 285)

14:02
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Lecture 5, Part 3 (CS 285)

14:52
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Lecture 5, Part 4 (CS 285)

15:41
10

Lecture 6, Part 1 (CS 285)

25:13
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Lecture 6, Part 2 (CS 285)

17:29

CS 285: Lecture 2, Imitation Learning. Part 3

Sergey LevineUC Berkeley

Associate Professor of Electrical Engineering and Computer Sciences

32:23·2023·graduate level

This lecture segment systematically presents advanced imitation learning algorithms, delving into theoretical foundations of generative adversarial imitation learning (GAIL) and its practical implications for robust policy learning.

Systems & CSAlgorithms & Data StructuresReinforcement LearningImitation LearningBehavioral Cloning
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CS 285: Lecture 2, Imitation Learning. Part 2

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CS 285: Lecture 4, Part 1

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