Q-Learning

Q-Learning is a type of reinforcement learning algorithm that aims to find the best action to take given the current state. It works by learning a "Q-function," which estimates the expected cumulative reward for taking a specific action in a particular state and following the optimal policy thereafter. This Q-function is iteratively updated based on the agent's experiences, allowing it to learn the optimal policy without needing a model of the environment.

Visit the following resources to learn more:

• @article@An Introduction to Q-Learning: A Tutorial For Beginners
• @article@A Gentle Introduction to Q-Learning
• @video@What is Q-Learning (back to basics)