Function Approximation
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Why FA, policy gradient update, DQN exploration, experience replay, and actor-critic — with explanations.
State and transition count for 10×10 gridworld; function approximation.
5 quick questions after Chapters 21–25 of Volume 3. Check you're ready to continue.
Memory for Backgammon Q-table; necessity of function approximation.
Linear FA with tile coding for MountainCar; semi-gradient SARSA.
Designing state and state-action features for linear value approximation.
15 short drill problems for Volume 3: linear FA, semi-gradient TD, DQN, replay buffer, target network, Double DQN, and dueling networks.
Review Volume 2 tabular methods and preview Volume 3. From Q-tables to neural network function approximation.