Introduction: One kind of machine learning called Reinforcement Learning (RL) enables an agent to learn how to behave in an environment by performing certain activities and seeing the results of such acts. As opposed to supervised learning, which involves training the model on a fixed dataset, educating an agent by having it interact with its surroundings. What is Reinforcement Learning? Within the discipline of reinforcement learning in machine learning, an agent gains decision-making skills by acting in a way that maximizes cumulative rewards. It is inspired by behavioral psychology, where learning is driven by rewards and punishments. Key Concepts in Reinforcement Learning: 1. Exploration vs. Exploitation: Exploration involves trying new actions to discover their effects, while Exploitation means choosing actions that are known ...