Reinforcement Learning tasks are learning problems where the desired behavior is not known; only sparse feedback on how well the agent is doing is provided. Reinforcement Learning techniques include the value-function and policy iteration methods on the. Our research using this approach includes real-world applications of packet routing and satellite communication, as described below.

See our Neuroevolution area for a different approach to learning with sparse feedback.