Reinforcement Learning: Bellman Optimality Equation and the Q-function

In this video, I explain the Bellman Optimality Equation and the Q-function, two core concepts in reinforcement learning. We’ll start by asking an important question: What happens when acting greedily no longer improves a policy? This leads us to the idea of optimal policies and the value function that satisfies the Bellman Optimality Equation. The video includes: A clear explanation of the Q-function How the Bellman Optimality Equation is used in learning A simple, step-by-step numerical example of computing a Q-value How to extract a policy from Q-value