Richard S. Sutton
Impact in
- Artificial Intelligence top 0.01%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Neural Networks and Applications
- Computational Theory and Mathematics top 0.02%
- Adaptive Dynamic Programming Control
Papers in
-
- Reinforcement Learning in Robotics 68
- Evolutionary Algorithms and Applications 22
- Neural Networks and Applications 15
- Artificial Intelligence in Games 11
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- Adaptive Dynamic Programming Control 12
- Co-authors
- Andy Barto (2 shared papers)Andrew G. Barto (22 shared papers)Satinder Singh (10 shared papers)Doina Precup (16 shared papers)David McAllester (2 shared papers)Yishay Mansour (1 shared paper)David Silver (8 shared papers)Hamid Reza Maei (5 shared papers)
- Journals
- Machine Learning (7 papers)Adaptive Behavior (4 papers)Artificial Intelligence (3 papers)Biological Cybernetics (3 papers)Behavioral Neuroscience (3 papers)
- Partner nations
- CanadaUnited StatesAustralia
In The Last Decade
Richard S. Sutton
140 papers receiving 39.4k citations
Richard S. Sutton's Hit Papers
Peers
Comparison fields: 5 of 202
- Artificial Intelligence 20.9k
- Computational Theory and Mathematics 5.1k
- Cognitive Neuroscience 5.9k
- Control and Systems Engineering 7.3k
- Management Science and Operations Research 3.9k
Countries citing papers authored by Richard S. Sutton
This map shows the geographic impact of Richard S. Sutton's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Richard S. Sutton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard S. Sutton more than expected).
Fields of papers citing papers by Richard S. Sutton
This network shows the impact of papers produced by Richard S. Sutton. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Richard S. Sutton. The network helps show where Richard S. Sutton may publish in the future.
Co-authors
The 25 scholars most cited alongside Richard S. Sutton, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 144 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reinforcement Learning: An Introduction Hit paper breakdown → | 1998 | 19107 |
| 2 | Introduction to Reinforcement Learning Hit paper breakdown → | 1998 | 4350 |
| 3 | Policy Gradient Methods for Reinforcement Learning with Function Approximation Hit paper breakdown → | 1999 | 2779 |
| 4 | Learning to Predict by the Methods of Temporal Differences Hit paper breakdown → | 1988 | 2353 |
| 5 | Learning to predict by the methods of temporal differences Hit paper breakdown → | 1988 | 2032 |
| 6 | Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning Hit paper breakdown → | 1999 | 1685 |
| 7 | Toward a modern theory of adaptive networks: Expectation and prediction. Hit paper breakdown → | 1981 | 1018 |
| 8 | Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding Hit paper breakdown → | 1995 | 649 |
| 9 | Temporal credit assignment in reinforcement learning Hit paper breakdown → | 1984 | 444 |
| 10 | 1991 | 383 | |
| 11 | Time-Derivative Models of Pavlovian Reinforcement | 1990 | 363 |
| 12 | 1996 | 362 | |
| 13 | 1992 | 342 | |
| 14 | 2009 | 260 | |
| 15 | Learning and Sequential Decision Making | 1989 | 246 |
| 16 | 1992 | 239 | |
| 17 | 2005 | 237 | |
| 18 | Predictive Representations of State | 2001 | 237 |
| 19 | Reward is enough Hit paper breakdown → | 2021 | 227 |
| 20 | Eligibility Traces for Off-Policy Policy Evaluation | 2000 | 174 |
About Richard S. Sutton
Richard S. Sutton is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Cognitive Neuroscience and Control and Systems Engineering, having authored 144 papers that have together received 41.3k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (68 papers), Evolutionary Algorithms and Applications (22 papers), Neural Networks and Applications (15 papers), Advanced Bandit Algorithms Research (15 papers), Adaptive Dynamic Programming Control (12 papers), Neural dynamics and brain function (12 papers), Artificial Intelligence in Games (11 papers) and Neuroscience and Neural Engineering (8 papers). The work is most often cited by research in Artificial Intelligence (20.9k citations), Computational Theory and Mathematics (5.1k citations), Cognitive Neuroscience (5.9k citations), Control and Systems Engineering (7.3k citations) and Management Science and Operations Research (3.9k citations). Richard S. Sutton has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Andy Barto, Andrew G. Barto, Satinder Singh, Doina Precup, David McAllester, Yishay Mansour, David Silver, Hamid Reza Maei, Patrick M. Pilarski and Michael L. Littman. Their work appears in journals such as Machine Learning, Adaptive Behavior, Artificial Intelligence, Biological Cybernetics and Behavioral Neuroscience.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.