2026 Richard S. Sutton: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	78	1158	1121	37	32	223	108759

Research.com Recognitions

2025 - Research.com Computer Science in Canada Leader Award
2023 - Research.com Computer Science in Canada Leader Award
2022 - Research.com Computer Science in Canada Leader Award
2001 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to many topics in machine learning, including reinforcement learning, temporal difference techniques, and neural networks.

Overview

Richard S. Sutton is affiliated with the University of Alberta in Canada and has contributed extensively to research in the field of computer science, with a focus on artificial intelligence and its related subfields.

The main fields of study for this scientist include:

Computer Science

The subfields of study cover:

Artificial Intelligence
Management Science and Operations Research
Computational Theory and Mathematics
Biomedical Engineering
Computer Networks and Communications

Research topics explored are diverse and include:

Reinforcement Learning in Robotics
Advanced Bandit Algorithms Research
Domain Adaptation and Few-Shot Learning
Neural Networks and Applications
Explainable Artificial Intelligence (XAI)
Optimization and Search Problems
Data Stream Mining Techniques

Among frequent coauthors are:

Sina Ghiassian
Yi Wan
Shibhansh Dohare
Kenny Young
Marlos C. Machado

Publication venues where this scientist has been active include:

arXiv (Cornell University)
Artificial Intelligence
Proceedings of the AAAI Conference on Artificial Intelligence
Journal of Artificial General Intelligence
Nature

Recent papers demonstrate engagement with a variety of aspects in artificial intelligence and machine learning. Notable works include:

"Reward is enough", 2021, Artificial Intelligence
"Special Issue "On Defining Artificial Intelligence"-Commentaries and Author's Response", 2020, Journal of Artificial General Intelligence
"Loss of plasticity in deep continual learning", 2024, Nature
"Policy iterations for reinforcement learning problems in continuous time and space - Fundamental theory and methods", 2021, Automatica
"Looking Back on the Actor-Critic Architecture", 2020, IEEE Transactions on Systems Man and Cybernetics Systems

Recognition includes being named Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2001 for contributions to machine learning, reinforcement learning, temporal difference techniques, and neural networks.

Best Publications

Reinforcement Learning: An Introduction

R.S. Sutton;A.G. Barto

50110
Citations
Learning to Predict by the Methods of Temporal Differences

Richard S. Sutton

6853
Citations
Introduction to Reinforcement Learning

Richard S. Sutton;Andrew G. Barto

6763
Citations
Policy Gradient Methods for Reinforcement Learning with Function Approximation

Richard S Sutton;David A. McAllester;Satinder P. Singh;Yishay Mansour

6279
Citations
Neuronlike adaptive elements that can solve difficult learning control problems

Andrew G. Barto;Richard S. Sutton;Charles W. Anderson

4910
Citations
Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning

Richard S. Sutton;Doina Precup;Satinder Singh

3975
Citations
Integrated architecture for learning, planning, and reacting based on approximating dynamic programming

Richard S. Sutton

2020
Citations
Toward a modern theory of adaptive networks: Expectation and prediction.

Richard S. Sutton;Andrew G. Barto

1851
Citations
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding

Richard S Sutton

1696
Citations
Neural networks for control

W. Thomas Miller;Richard S. Sutton;Paul J. Werbos

1582
Citations
Temporal credit assignment in reinforcement learning

Richard Stuart Sutton

1081
Citations
Reinforcement learning with replacing eligibility traces

Satinder P. Singh;Richard S. Sutton

991
Citations
Dyna, an integrated architecture for learning, planning, and reacting

Richard S. Sutton

955
Citations
Reinforcement learning is direct adaptive optimal control

R.S. Sutton;A.G. Barto;R.J. Williams

852
Citations
Time-Derivative Models of Pavlovian Reinforcement

Richard S. Sutton;Andrew G. Barto

798
Citations
Natural actor-critic algorithms

Shalabh Bhatnagar;Richard S. Sutton;Mohammad Ghavamzadeh;Mark Lee

728
Citations
Eligibility Traces for Off-Policy Policy Evaluation

Doina Precup;Richard S. Sutton;Satinder P. Singh

680
Citations
Predictive Representations of State

Michael L. Littman;Richard S Sutton

660
Citations
A Menu of Designs for Reinforcement Learning Over Time

Unknown

652
Citations
Fast gradient-descent methods for temporal-difference learning with linear function approximation

Richard S. Sutton;Hamid Reza Maei;Doina Precup;Shalabh Bhatnagar

649
Citations
First results with Dyna, an integrated architecture for learning, planning and reacting

Richard S. Sutton

76
Citations

Frequent Co-Authors

Andrew G. Barto University of Massachusetts Amherst

Doina Precup McGill University

Paul J. Werbos University of Memphis

Satinder Singh DeepMind (United Kingdom)

Csaba Szepesvári University of Alberta

E. James Kehoe University of New South Wales

David Silver DeepMind (United Kingdom)

Charles W. Anderson Colorado State University

Peter Stone The University of Texas at Austin

Michael Bowling University of Alberta

External Links

Wikipedia of Richard S. Sutton Personal website of Richard S. Sutton Google Scholar page

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