Reinforcement Learning is present in various aspects of daily life. For instance, a child learning to ride a bicycle uses trial and error (exploration) to discover the right balance and control (exploitation). Similarly, a thermostat in a smart home learns when to adjust heating or cooling based on comfort and energy efficiency goals.