A trial and error machine learning technique used in applications such as robotics, self-driving cars and gaming. Reinforcement learning enables an AI agent to make decisions based on rewards and penalties. A positive outcome of an action is rewarded while a negative outcome is penalized. Over time, the AI learns to improve its performance based on the feedback. See
AI agent.