Reinforcement Learning, Part ii: Partial Observability, Offline Data, and DTRs
What changes with hidden states or fixed datasets, and how history-based offline learning connects to DTRs.
What changes with hidden states or fixed datasets, and how history-based offline learning connects to DTRs.
MDP assumptions, Bellman equations, a value-iteration proof, and the main families of RL methods.