Rich Sutton

Rich Sutton is a Professor in Computing Science at the University of Alberta and holds the AITF Chair in Reinforcement Learning and Artificial Intelligence. His research seeks fundamental computational principles of intelligence, focusing on the interaction between agents and environments to understand goal-directed behavior, learning, and decision-making.

Research explores reinforcement learning algorithms, empirical knowledge representation, and reducing manual knowledge encoding. Educational background includes a PhD in Computer Science from the University of Massachusetts, an MS in Computer Science (UMass), and a BA in Psychology from Stanford University. Contributions include foundational work on temporal difference learning and reinforcement learning theory.

Research interests span artificial intelligence foundations, real-time learning systems, and connections between animal learning theory and machine learning algorithms.