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- VISTA simulator
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Classroom Contents
Reinforcement Learning - MIT 6.S191 Lecture 5
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- 1 - Introduction
- 2 - Classes of learning problems
- 3 - Definitions
- 4 - The Q function
- 5 - Deeper into the Q function
- 6 - Deep Q Networks
- 7 - Atari results and limitations
- 8 - Policy learning algorithms
- 9 - Discrete vs continuous actions
- 10 - Training policy gradients
- 11 - RL in real life
- 12 - VISTA simulator
- 13 - AlphaGo and AlphaZero and MuZero
- 14 - Summary
