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This lecture provides an overview of reinforcement learning, focusing on the BackUp diagram as a graphic representation of the steps an RL algorithm remembers. Topics covered include deep reinforcement learning, neural networks, policy branching probabilities, total expected reward, Bellman equation, SARSA algorithm, and the application of SARSA for estimating Q values.