Unlike other AI methods, reinforcement learning does not need pre-labeled data to learn.

Most AI models are like students memorizing flashcards with the answers already written on the back. That is called supervised learning. But reinforcement learning is different. It does not use pre-labeled datasets or human guides. Instead, the computer learns entirely from its own experience and trial-and-error. It plays the game or navigates the room, makes mistakes, and learns from the direct feedback of its own actions.