Richard S. Sutton - Wikipedia

Richard S. Sutton FRS FRSC is a Canadian computer scientist. He is a professor of computing science at the University of Alberta and a research scientist at Keen Technologies.[1] Sutton is considered one of the founders of modern computational reinforcement learning,[2] having several significant contributions to the field, including temporal difference learning and policy gradient methods.[3] Richard Sutton was born in Ohio, and grew up in Oak Brook, Illinois, a suburb of Chicago. Sutton received his B.A. in psychology from Stanford University in 1978 before taking an M.S. (1980) and Ph.D. (1984) in computer science from the University of Massachusetts Amherst under the supervision of Andrew Barto. His doctoral dissertation, Temporal Credit Assignment in Reinforcement Learning, introduced actor-critic architectures and temporal credit assignment.[4][3] He was influenced by Harry Klopf's work in the 1970s, which proposed that supervised learning is insufficient for AI or explaining int

Richard S. Sutton - Wikipedia Jump to content From Wikipedia, the free encyclopedia Computer scientist <br> USA until 2017<ref name=\"fedreg2017\" />"},"fields":{"wt":"{{Plainlist|\n* [[Artificial intelligence]]\n* [[Reinforcement learning]]\n* [[Machine learning]]\n* [[Cognitive science]]\n* [[Computer science]]<ref name=gs/>}}"},"workplaces":{"wt":"{{Plainlist|\n* [[University of Alberta]]\n* [[AT&T Labs]]\n* [[Google DeepMind]]\n* [[GTE]]\n* [[University of Massachusetts Amherst]]}}"},"thesis_title":{"wt":"Temporal credit assignment in reinforcement learning"},"thesis_url":{"wt":"http://inc

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