Reinforcement Learning

A training paradigm where an agent learns by interacting with an environment, taking actions, and receiving rewards or penalties based on the outcomes. Rather than learning from labeled examples, the agent discovers through trial and error what behaviors lead to the best cumulative reward, the approach behind game-playing AI systems like AlphaGo and robotic control systems.