L10 : Deep Reinforcement Learning: Function Approximation, DQN for Atari Games, DQN for Atari Games, MCTS for AlphaGo
Lecture Goals
- Know the role of function approximation in Q-learning
- Be able to understand the key innovations in the DQN model
- Identify the differences between Monte Carlo tree search vs Monte Carlo rollouts
- Be able to identify key compoments of the AlphaGo (and variants such as AlphaZero) Go playing agent