Reinforcement Learning (RL) is a special way that computers can learn how to make good decisions by trying things and learning from their mistakes.

Imagine playing a game you've never seen before. At first, you don’t know which moves are good or bad, so you just try things out. Every time you take an action, you get feedback.

If your action is good, you get points; if it’s bad, you might lose points or get no points at all. Over time, you start figuring out what moves are best, because you want to get more points.