Reinforcement Learning

A reinforcement learning agent is tasked with interacting with an unknown environment and learning, through trial and error, a policy that minimizes long-term cost or maximizes long term reward. Problems as diverse as game playing, robotic control, disease management or user experience management fit this model. Research at Duke addresses fundamental questions in reinforcement learning including algorithm design, sample complexity, feature selection and state space representation.