Reinforcement learning (RL), supervised learning, and unsupervised learning are three fundamental paradigms in the field of machine learning, each with distinct methodologies, objectives, and applications. Understanding these differences is important for leveraging their respective strengths in solving complex problems. Supervised Learning Supervised learning involves training a model on a labeled dataset, which means that each