COMPUTER FUNDAMENTALS

Detailed explanation-1: -Reinforcement learning doesn’t rely on labeled datasets: The agent isn’t told which actions to take or the optimal way of performing a task. RL uses rewards and penalties instead of labels associated with each decision in datasets to signal whether a taken action is good or bad.

Detailed explanation-2: -Reinforcement learning is decision dependent. So, labels are given to sequences of dependent decisions. Supervised learning the choices are independent of each other, so labels are assigned to each decision.