Richard S. Sutton

1. Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
   1999/08/01 by Richard S. Sutton, Doina Precup, Satinder Singh · 370 citations
   Computer Science · #Reinforcement Learning in Robotics #Formal Methods in Verification #Advanced Software Engineering Methodologies
2. Reinforcement Learning: An Introduction
   1998/09/01 by Richard S. Sutton, R.S. Sutton, A.G. Barto +1 · 578 citations
   Computer Science · Psychology · #Behavioral and Psychological Studies #Neural Networks and Applications #Reinforcement Learning in Robotics
3. The Alberta Plan for AI Research
   2022/08/23 by Richard S. Sutton, Michael Bowling, Sutton, Richard S. +3 · 6 voices · 4 citations
   #cs.AI #cs.LG
4. Neuronlike adaptive elements that can solve difficult learning control problems
   1983/09/01 by Andrew G. Barto, Richard S. Sutton, Charles W. Anderson · 51 citations
   Computer Science · Biochemistry, Genetics and Molecular Biology · #Adaptive Dynamic Programming Control #Zebrafish Biomedical Research Applications
5. Continual Backprop: Stochastic Gradient Descent with Persistent Randomness
   2021/08/13 by Shibhansh Dohare, Richard S. Sutton, Dohare, Shibhansh +3 · 8 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Adversarial Robustness in Machine Learning
6. Learning and Planning in Average-Reward Markov Decision Processes
   2020/06/29 by Yi Wan, Abhishek Naik, Wan, Yi +3 · 8 citations
   Computer Science · Decision Sciences · #Reinforcement Learning in Robotics #Advanced Bandit Algorithms Research #Optimization and Search Problems
7. Dyna-Style Planning with Linear Function Approximation and Prioritized\n Sweeping
   2012/06/13 by Richard S. Sutton, Sutton, Richard S., Csaba Szepesvári +6 · 4 citations
   Computer Science · Decision Sciences · #AI-based Problem Solving and Planning #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Electrical engineering #Formal Methods in Verification #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Robotic Path Planning Algorithms #Systems and Control (eess.SY) #electronic engineering #information engineering
8. Reward Centering
   2024/05/16 by Abhishek Naik, Naik, Abhishek, Yi Wan +5 · 5 citations
   Computer Science · Decision Sciences · Psychology · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #Behavioral and Psychological Studies #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
9. Average-Reward Off-Policy Policy Evaluation with Function Approximation
   2021/01/08 by Shangtong Zhang, Yi Wan, Zhang, Shangtong +5 · 4 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Optimization and Search Problems #Reinforcement Learning in Robotics
10. Value-aware Importance Weighting for Off-policy Reinforcement Learning
    2023/06/27 by Kristopher De Asis, Eric Graves, De Asis, Kristopher +3 · 2 citations
    Computer Science · #Reinforcement Learning in Robotics
11. Discounted Reinforcement Learning Is Not an Optimization Problem
    2019/10/04 by Abhishek Naik, Naik, Abhishek, Roshan Shariff +7 · 1 citation
    Business, Management and Accounting · Computer Science · #Adaptive Dynamic Programming Control #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Reinforcement Learning in Robotics #Supply Chain and Inventory Management
12. Learning Sparse Representations Incrementally in Deep Reinforcement Learning
    2019/12/09 by J. Fernando Hernandez-Garcia, Richard S. Sutton, Hernandez-Garcia, J. Fernando +1 · 1 citation
    Computer Science · Decision Sciences · #Reinforcement Learning in Robotics #Evolutionary Algorithms and Applications #Advanced Bandit Algorithms Research
13. Understanding the Pathologies of Approximate Policy Evaluation when\n Combined with Greedification in Reinforcement Learning
    2020/10/28 by Kenny Young, Richard S. Sutton, Young, Kenny +1 · 1 citation
    Computer Science · #Reinforcement Learning in Robotics
14. Does the Adam Optimizer Exacerbate Catastrophic Forgetting?
    2021/02/15 by Dylan R. Ashley, Ashley, Dylan R., Sina Ghiassian +3 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
15. A First Empirical Study of Emphatic Temporal Difference Learning
    2017/05/11 by Sina Ghiassian, Banafsheh Rafiee, Ghiassian, Sina +3 · 1 citation
    Computer Science · #Adaptive Dynamic Programming Control #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Reinforcement Learning in Robotics
16. An Idiosyncrasy of Time-discretization in Reinforcement Learning
    2024/06/21 by Kris De Asis, De Asis, Kris, Richard S. Sutton +1 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #I.2.6 #I.2.9 #Machine Learning (cs.LG)
17. Average-Reward Learning and Planning with Options
    2021/10/26 by Yi Wan, Abhishek Naik, Wan, Yi +3 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Receptor Mechanisms and Signaling #Reinforcement Learning in Robotics
18. Planning with Expectation Models
    2019/04/02 by Yi Wan, Wan, Yi, Zaheer Abbas +7 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics