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an American computer scientist and [[Artificial Intelligence|AI]]-researcher. Since 2003, Richard S. Sutton is a professor in the Department of Computing Science <ref>[http://www.cs.ualberta.ca/ Home | Department of Computing Science]</ref> at the [[University of Alberta]] and is principal investigator of the [[Reinforcement Learning]] and [[Artificial Intelligence]] (RLAI) <ref>[http://rlai.cs.ualberta.ca/RLAI/ualberta.html Reinforcement Learning and Artificial Intelligence (RLAI)]</ref> group. Rich's research interests center on the [[Learning|learning]] problems facing a decision-maker interacting with its environment, which he sees as central to artificial intelligence. He is the author of the original paper on [[Temporal Difference Learning]] <ref>[[Richard Sutton]] ('''1988'''). ''Learning to Predict by the Methods of Temporal Differences''. [https://en.wikipedia.org/wiki/Machine_Learning_(journal) Machine Learning], Vol. 3, No. 1</ref> and, with [[Andrew Barto]], of the textbook ''Reinforcement Learning: An Introduction'' <ref>[http://incompleteideas.net/book/the-book.html Reinforcement Learning: An Introduction] ebook by Richard Sutton and [[Andrew Barto]]</ref> . He is also interested in animal learning psychology, in [https://en.wikipedia.org/wiki/Connectionism connectionist] networks, and generally in systems that continually improve their representations and models of the world <ref>[http://incompleteideas.net/BriefBio.html Brief Biography for Richard Sutton]</ref> .

* [[Richard Sutton]], [[Csaba Szepesvári]], [[Hamid Reza Maei]] ('''2008'''). ''A Convergent O(n) Algorithm for Off-policy Temporal-difference Learning with Linear Function Approximation''.[https://dblp.uni-trier.de/db/conf/nips/nips2008.html#SuttonSM08 NIPS 2008], [https://proceedings.neurips.cc/paper/2008/file/e0c641195b27425bb056ac56f8953d24-Paper.pdf pdf]

* [[Hamid Reza Maei]], [[Csaba Szepesvári]], [[Shalabh Bhatnagar]], [[Doina Precup]], [[David Silver]], [[Richard Sutton]] ('''2009'''). ''Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation.'' . [https://dblp.uni-trier.de/db/conf/nips/nips2009.html#MaeiSBPSS09 NIPS 222009], MIT Press[https://papers.nips.cc/paper/2009/file/3a15c7d0bbe60300a39f76f8a5ba6896-Paper.pdf pdf]* [[Richard Sutton]], [[Hamid Reza Maei]], [[Doina Precup]], [[Shalabh Bhatnagar]], [[David Silver]], [[Csaba Szepesvári]], [[Eric Wiewiora]]. ('''2009'''). ''[https://dl.acm.org/doi/10.1145/1553374.1553501 Fast Gradient-Descent Methods for Temporal-Difference Learning with Linear Function Approximation]''. ICML-09, [httphttps://wwwdblp.sztakiuni-trier.hude/db/~szcsabaconf/papersicml/GTD-ICML09icml2009.pdf pdfhtml#SuttonMPBSSW09 ICML 2009]

* [[Hamid Reza Maei]], [[Csaba Szepesvári]], [[Shalabh Bhatnagar]], [[Richard Sutton]] ('''2010'''). ''Toward Off-Policy Learning Control with Function Approximation''. [httphttps://wwwdblp.incompleteideasuni-trier.netde/db/conf/suttonicml/publicationsicml2010.html#GQ MaeiSBS10 ICML 2010], [https://icml.cc/Conferences/2010/papers/627.pdf pdf]* [[Hamid Reza Maei]], [[Richard Sutton]] ('''2010'''). ''[https://www.researchgate.net/publication/215990384_GQlambda_A_general_gradient_algorithm_for_temporal-difference_prediction_learning_with_eligibility_traces GQ(λ): A general gradient algorithm for temporal-difference prediction learning with eligibility traces]''. In Proceedings of the Third Conference on Artificial General Intelligence[https://agi-conf.org/2010/ AGI 2010]