Reinforcement Learning
Reinforcement learning is a subfield of machine learning concerned with how agents ought to take actions in an environment to maximize cumulative reward. It is distinguished by its focus on learning from interaction, using trial and error, and is widely applied in robotics, game playing, and autonomous systems.
