This episode gives a general introduction into the field of Reinforcement Learning:
- High level description of the field
- Policy gradients
- Biggest challenges (sparse rewards, reward shaping, ...)
This video forms the basis for a series on RL where I will dive much deeper into technical details of state-of-the-art methods for RL.
Links:
- “Pong from Pixels - Karpathy“:
- Concept networks for grasp & stack (Paper with heavy reward shaping):
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