Q-Learning from Scratch: Navigating the Frozen...

Imagine you're standing on a frozen lake. Your goal is on the far side, but there are holes in the ice — fall in and it's game over. Worse, the ice is slippery: when you try to go right, you might slide up or down instead. You have no map, no instructions. All you can do is try, fail, and gradually learn which moves lead to safety. This is exactly what Q-learning solves. The agent learns a value for every state-action pair — "how good is it to take action A from state S?" — purely from trial and