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Author Information
Alborz Geramifard (Facebook AI)
Michael Bowling (DeepMind / University of Alberta)
Martin A Zinkevich (Yahoo! Inc.)
Rich Sutton (DeepMind, U Alberta)
Richard S. Sutton is a professor and iCORE chair in the department of computing science at the University of Alberta. He is a fellow of the Association for the Advancement of Artificial Intelligence and co-author of the textbook "Reinforcement Learning: An Introduction" from MIT Press. Before joining the University of Alberta in 2003, he worked in industry at AT&T and GTE Labs, and in academia at the University of Massachusetts. He received a PhD in computer science from the University of Massachusetts in 1984 and a BA in psychology from Stanford University in 1978. Rich's research interests center on the learning problems facing a decision-maker interacting with its environment, which he sees as central to artificial intelligence. He is also interested in animal learning psychology, in connectionist networks, and generally in systems that continually improve their representations and models of the world.
More from the Same Authors
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2019 Workshop: The third Conversational AI workshop – today's practice and tomorrow's potential »
Alborz Geramifard · Jason Williams · Bill Byrne · Asli Celikyilmaz · Milica Gasic · Dilek Hakkani-Tur · Matt Henderson · Luis Lastras · Mari Ostendorf -
2018 Workshop: The second Conversational AI workshop – today's practice and tomorrow's potential »
Alborz Geramifard · Jason Williams · Larry Heck · Jim Glass · Milica Gasic · Dilek Hakkani-Tur · Steve Young · Lazaros Polymenakos · Y-Lan Boureau · Maxine Eskenazi -
2017 Workshop: Conversational AI - today's practice and tomorrow's potential »
Alborz Geramifard · Jason Williams · Larry Heck · Jim Glass · Antoine Bordes · Steve Young · Gerald Tesauro -
2016 Poster: The Forget-me-not Process »
Kieran Milan · Joel Veness · James Kirkpatrick · Michael Bowling · Anna Koop · Demis Hassabis -
2016 Poster: Deep Learning Games »
Dale Schuurmans · Martin A Zinkevich -
2015 Tutorial: Introduction to Reinforcement Learning with Function Approximation »
Richard Sutton -
2014 Workshop: Representation and Learning Methods for Complex Outputs »
Richard Zemel · Dale Schuurmans · Kilian Q Weinberger · Yuhong Guo · Jia Deng · Francesco Dinuzzo · Hal Daumé III · Honglak Lee · Noah A Smith · Richard Sutton · Jiaqian YU · Vitaly Kuznetsov · Luke Vilnis · Hanchen Xiong · Calvin Murdock · Thomas Unterthiner · Jean-Francis Roy · Martin Renqiang Min · Hichem SAHBI · Fabio Massimo Zanzotto -
2014 Poster: Universal Option Models »
hengshuai yao · Csaba Szepesvari · Richard Sutton · Joseph Modayil · Shalabh Bhatnagar -
2014 Poster: Weighted importance sampling for off-policy learning with linear function approximation »
Rupam Mahmood · Hado P van Hasselt · Richard Sutton -
2013 Workshop: Advances in Machine Learning for Sensorimotor Control »
Thomas Walsh · Alborz Geramifard · Marc Deisenroth · Jonathan How · Jan Peters -
2012 Workshop: Bayesian Nonparametric Models For Reliable Planning And Decision-Making Under Uncertainty »
Jonathan How · Lawrence Carin · John Fisher III · Michael Jordan · Alborz Geramifard -
2012 Poster: Sketch-Based Linear Value Function Approximation »
Marc Bellemare · Joel Veness · Michael Bowling -
2012 Poster: Tractable Objectives for Robust Policy Optimization »
Katherine Chen · Michael Bowling -
2011 Poster: Variance Reduction in Monte-Carlo Tree Search »
Joel Veness · Marc Lanctot · Michael Bowling -
2011 Invited Talk (Posner Lecture): Learning About Sensorimotor Data »
Richard Sutton -
2010 Workshop: Learning and Planning from Batch Time Series Data »
Daniel Lizotte · Michael Bowling · Susan Murphy · Joelle Pineau · Sandeep Vijan -
2009 Poster: Multi-Step Dyna Planning for Policy Evaluation and Control »
Hengshuai Yao · Richard Sutton · Shalabh Bhatnagar · Dongcui Diao · Csaba Szepesvari -
2009 Poster: Strategy Grafting in Extensive Games »
Kevin G Waugh · Nolan Bard · Michael Bowling -
2009 Poster: Monte Carlo Sampling for Regret Minimization in Extensive Games »
Marc Lanctot · Kevin G Waugh · Martin A Zinkevich · Michael Bowling -
2009 Poster: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2009 Spotlight: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2008 Poster: A computational model of hippocampal function in trace conditioning »
Elliot A Ludvig · Richard Sutton · Eric Verbeek · James Kehoe -
2008 Demonstration: RL-Glue: From Grid Worlds to Sensor Rich Robots »
Brian Tanner · Adam M White · Richard Sutton -
2008 Session: Oral session 3: Learning from Reinforcement: Modeling and Control »
Michael Bowling -
2008 Poster: A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approxi »
Richard Sutton · Csaba Szepesvari · Hamid R Maei -
2007 Spotlight: Incremental Natural Actor-Critic Algorithms »
Shalabh Bhatnagar · Richard Sutton · Mohammad Ghavamzadeh · Mark P Lee -
2007 Spotlight: Stable Dual Dynamic Programming »
Tao Wang · Daniel Lizotte · Michael Bowling · Dale Schuurmans -
2007 Poster: Incremental Natural Actor-Critic Algorithms »
Shalabh Bhatnagar · Richard Sutton · Mohammad Ghavamzadeh · Mark P Lee -
2007 Poster: Stable Dual Dynamic Programming »
Tao Wang · Daniel Lizotte · Michael Bowling · Dale Schuurmans -
2007 Spotlight: Regret Minimization in Games with Incomplete Information »
Martin A Zinkevich · Michael Johanson · Michael Bowling · Carmelo Piccione -
2007 Poster: Regret Minimization in Games with Incomplete Information »
Martin A Zinkevich · Michael Johanson · Michael Bowling · Carmelo Piccione -
2007 Poster: Computing Robust Counter-Strategies »
Michael Johanson · Martin A Zinkevich · Michael Bowling