Learning Control

Learning control refers to the process of acquiring a control strategy for a particular control system and a particular task by trial and error. Learning control is usually distinguished from adaptive control in that the learning system is permitted to fail during the process of learning. In contrast, adaptive control emphasizes single trial convergence without failure. Thus, learning control resembles the way that humans and animals acquire new movement strategies, while adaptive control is a special case of learning control that fulfills stringent performance constraints, e.g., as needed in life-critical systems like airplanes and industrial robots. In general, the control system can be any system that changes its state in response to a control signal, e.g., a web page with a hyperlink, a car, or a robot.