Learning from experience

Richard S. Sutton, FRS, FRSC, is one of the pioneers of reinforcement learning, an approach to artificial and natural intelligence that emphasizes learning and planning from sample experience, and a field in which he continues to lead the world. He is most interested in understanding what it means to be intelligent, to predict and influence the world, to learn, perceive, act, and think. Over his career, he has made many significant contributions to the field, including the theory of temporal-difference learning, the actor-critic (policy gradient) class of algorithms, the Dyna architecture (integrating learning, planning and reacting), the Horde architecture, and gradient and emphatic temporal-difference algorithms – among other advancements. Richard currently seeks to extend reinforcement learning ideas to an empirically grounded approach to knowledge representation based on prediction.

In 2023, Richard teamed up with John Carmack, visionary software engineer and founder of Keen Technologies, to focus and advance the science of artificial general intelligence. Through this work, documented in part in The Alberta Plan, Richard seeks to understand and create long-lived computation agents that interact with a vastly more complex world and come to predict and control their sensory input signals. 

Richard has been named a Fellow of the Royal Society, Fellow of the Royal Society of Canada, the Association for the Advancement of Artificial Intelligence (AAAI), and the Canadian Artificial Intelligence Association (CAIAC), where he also received a Lifetime Achievement Award in 2018. Richard has been an academic supervisor to almost 60 early-career researchers, and his publications have been cited more than 93,000 times. Richard has been featured in popular publications such as Science, the Economist, the New York Times, the Wall Street Journal, and Bloomberg’s Hello World.