Richard O. Sutton

Richard S. Sutton is a Canadian computer scientist and professor of computing science at the University of Alberta, recognized as one of the founders of modern computational reinforcement learning. He pioneered temporal difference learning, policy gradient methods, and actor-critic architectures, and co-authored the seminal textbook on reinforcement learning with Andrew Barto. In 2024, he received the Turing Award for developing the foundations of reinforcement learning.[1][3][4]