An Introduction to Q-Learning Part 2/2

This post details the Q-Learning algorithm, an off-policy value-based method using TD learning. It explains the Q-function and Q-table, the Q-Learning pseudocode (initialization, epsilon-greedy strategy, action execution, and Q-value update), and the distinction between off-policy and on-policy learning. A practical example with a maze scenario illustrates the algorithm's application.