Reinforcement Learning

Instead of learning only from labeled examples, a reinforcement-learning system interacts with an environment and learns a strategy from feedback over time. It is used in control, robotics, games, optimization, and some model-alignment techniques. Understanding the concept helps practitioners choose training methods, evaluate model quality, and reduce errors when predictions are used in production systems.