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

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related reading

• Rich Sutton's Home Pageincompleteideas.net
• Rich Sutton's Home Pageincompleteideas.net
• Ajay Agrawal on X: "The more I reflect on @maxsbennett 's new book "A Brief History of Intelligence" the more I think it will become a milestone reference in the race to #AGI. His contribution is a novel series of insights made by linking dx.com
• Richard Sutton – Father of RL thinks LLMs are a dead enddwarkesh.com
• Richard Sutton – Father of RL thinks LLMs are a dead enddwarkesh.com
• SuttonBartoIPRLBook2ndEd.pdfweb.stanford.edu
• A (Long) Peek into Reinforcement Learning | Lil'Loglilianweng.github.io
• Reinforcement learning - Wikipediaen.wikipedia.org
• Joseph Suarez 🐡 (@jsuarez) on Xx.com
• Deep Reinforcement Learning: Pong from Pixelskarpathy.github.io
• Jubayer Ibn Hamidjubayer-ibn-hamid.github.io
• Juergen Schmidhuber's home page - Universal Artificial Intelligence - AI - Deep Learning - Recurrent Neural Networks - Computer Vision - Object Detection - Image segmentation - GANs - Transformers with linearized self-attention - Goedel Macpeople.idsia.ch