Reinforcement Learning refers to a machine learning paradigm where agents learn optimal behaviors through trial-and-error interactions with an environment, receiving rewards or penalties for their actions and gradually improving their decision-making strategies over time. This approach mimics how humans and animals learn from experience, enabling artificial intelligence systems to master complex tasks like game playing,