An Introduction to Q-Learning Part 1

This post introduces the core concepts of value-based Reinforcement Learning methods. It defines state-value and action-value functions, explains their relationship to policies, and introduces the Bellman Equation for simplifying value estimation. It also contrasts Monte Carlo methods with Temporal Difference learning, setting the stage for Q-Learning.