Reinforcement Learning: Q-Learning

This lecture introduces the concept of reinforcement learning, focusing on Q-Learning as a model-free method for agents to learn by trial-and-error. It covers the exploration-exploitation trade-off, action values, and policies. The lecture also discusses the convergence properties of Q-Learning, the importance of human-compatible AI, and the impact of algorithms on society.