This lecture covers the concepts of Monte Carlo Tree Search (MCTS) and Alpha Zero, two key algorithms in deep reinforcement learning. It explains how MCTS involves selection, expansion, simulation, and backpropagation, while Alpha Zero utilizes visit counts, action values, and prior action probabilities to make decisions in games like Chess, Shogi, and Go.