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Rich Sutton March 13, 2019 The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. The ultimate reason for this is Moore's law, or rather its generalization of continued exponentially falling cost per unit of computation. Most AI research has been conducted as if the computation ava
Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto Second Edition (see here for the first edition) MIT Press, Cambridge, MA, 2018 Buy from Amazon Errata and Notes Full Pdf Trimmed for viewing on computers (latest release April 26, 2022) Code Solutions -- send in your solutions for a chapter, get the official ones back Slides and Other Teaching Aids Links to pdfs of much
Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto Second Edition (see here for the first edition) MIT Press, Cambridge, MA, 2018 Buy from Amazon Errata and Notes Full Pdf Without Margins Code Solutions -- send in your solutions for a chapter, get the official ones back (currently incomplete) Slides and Other Teaching Aids Links to pdfs of the literature sources cited i
Richard S. Sutton, FRS FRSC Research Scientist, Keen Technologies Professor, Department of Computing Science, University of Alberta Principal Investigator, Reinforcement Learning and Artificial Intelligence Lab Chief Scientific Advisor, Alberta Machine Intelligence Institute (Amii) Senior Fellow, CIFAR Department of Computing Science 3-13 Athabasca Hall Edmonton, Alberta Canada T6G 2E8 email rsutt
Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto Second Edition (see here for the first edition) MIT Press, Cambridge, MA, 2018 Buy from Amazon Errata Full Pdf pdf without margins (good for ipad) New Code Old Code Solutions -- send in your solutions for a chapter, get the official ones back (currently incomplete) Teaching Aids Literature sources cited in the book Latex
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