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Satinder Singh

Active 1965–2026

297
Papers
32,955
Citations
74
h-index
205
i10-index

Citations

Citations per year for Satinder Singh1965: 1 citations1982: 2 citations1984: 1 citations1987: 1 citations1990: 2 citations1991: 5 citations1992: 11 citations1993: 5 citations1994: 6 citations1995: 16 citations1996: 12 citations1997: 32 citations1998: 52 citations1999: 70 citations2000: 99 citations2001: 152 citations2002: 184 citations2003: 171 citations2004: 218 citations2005: 293 citations2006: 320 citations2007: 406 citations2008: 380 citations2009: 374 citations2010: 356 citations2011: 411 citations2012: 441 citations2013: 411 citations2014: 419 citations2015: 434 citations2016: 553 citations2017: 726 citations2018: 1,099 citations2019: 1,585 citations2020: 1,879 citations2021: 1,850 citations2022: 1,162 citations2023: 1,100 citations2024: 900 citations2025: 676 citations2026: 212 citations1966–1981: no citations, so these years are not shown1983: no citations, so this year is not shown1985–1986: no citations, so these years are not shown1988–1989: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 4,948 citing papers, 30.6% of this breakdownChina: 2,284 citing papers, 14.1% of this breakdownUnited Kingdom: 1,286 citing papers, 7.9% of this breakdownCanada: 872 citing papers, 5.4% of this breakdownGermany: 759 citing papers, 4.7% of this breakdownFrance: 540 citing papers, 3.3% of this breakdownJapan: 460 citing papers, 2.8% of this breakdownAustralia: 368 citing papers, 2.3% of this breakdownIndia: 364 citing papers, 2.3% of this breakdownItaly: 364 citing papers, 2.2% of this breakdownNetherlands: 354 citing papers, 2.2% of this breakdownSouth Korea: 285 citing papers, 1.8% of this breakdown
0%30.6%Other 20.4%

Institutions

Fields

  • Computer Science67.7%
  • Engineering11.9%
  • Decision Sciences6.6%
  • Neuroscience2.9%
  • Psychology2.1%
  • Medicine1.9%
  • Other6.9%

Topics

  • Reinforcement Learning in Robotics15.5%
  • Advanced Bandit Algorithms Research3%
  • Evolutionary Algorithms and Applications2.8%
  • Topic Modeling2.4%
  • Robot Manipulation and Learning2.1%
  • Adaptive Dynamic Programming Control2%
  • Other72.2%

Coauthors

All papers

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  1. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning

    Authors: Richard S. Sutton, Doina Precup, Satinder Singh - Artificial Intelligence, Artif. Intell. 1999 cited by 3,146

  2. Policy Gradient Methods for Reinforcement Learning with Function Approximation

    Authors: Richard S. Sutton, David A. McAllester, Satinder Singh, Yishay Mansour - http://www.cis.upenn.edu/~mkearns/finread/Sutton.pdf, NIPS 1999 cited by 7,816

  3. Reward is enough

    Authors: David Silver, Satinder Singh, Doina Precup, Richard S. Sutton - Artificial Intelligence, Artif. Intell. 2021 cited by 385

  4. Genie: Generative Interactive Environments

    Authors: Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel - ICML 2024 cited by 709

  5. In-context Reinforcement Learning with Algorithm Distillation

    Authors: Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih - ICLR 2023 cited by 212

  6. Blockchain and Deep Learning for Secure Communication in Digital Twin Empowered Industrial IoT Network

    Authors: Prabhat Kumar, Randhir Kumar, Abhinav Kumar, A. Antony Franklin, Sahil Garg, Satinder Singh - IEEE Transactions on Network Science and Engineering, IEEE Trans. Netw. Sci. Eng. 2022 cited by 109

  7. Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms

    Authors: Satinder Singh, Tommi S. Jaakkola, Michael L. Littman, Csaba Szepesvári - Machine Learning, Mach. Learn. 1998 cited by 625

  8. Near-Optimal Reinforcement Learning in Polynomial Time

    Authors: Michael J. Kearns, Satinder Singh - Machine Learning, Mach. Learn. 1998 cited by 858

  9. Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization

    Authors: Richard L. Lewis, Andrew Howes, Satinder Singh - Topics in Cognitive Science, Top. Cogn. Sci. 2014 cited by 233

  10. Structured State Space Models for In-Context Reinforcement Learning

    Authors: Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani - Advances in Neural Information Processing Systems 36, NeurIPS 2023 cited by 152

  11. Communication-Efficient Personalized Federated Meta-Learning in Edge Networks

    Authors: Feng Yu, Hui Lin, Xiaoding Wang, Sahil Garg, Georges Kaddoum, Satinder Singh, Mohammad Mehedi Hassan - IEEE Transactions on Network and Service Management, IEEE Trans. Netw. Serv. Manag. 2023 cited by 34

  12. Mastering Board Games by External and Internal Planning with Language Models

    Authors: John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev - ICML 2025 cited by 31

  13. Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective

    Authors: Satinder Singh, Richard L. Lewis, Andrew G. Barto, Jonathan Sorg - IEEE Transactions on Autonomous Mental Development, IEEE Trans. Auton. Ment. Dev. 2010 cited by 412

  14. Behaviour Suite for Reinforcement Learning

    Authors: Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvári, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt - ICLR 2020 cited by 212

  15. Intrinsically Motivated Reinforcement Learning

    Authors: Satinder Singh, Andrew G. Barto, Nuttapong Chentanez - OSD or Non-Service DoD Agency, NIPS 2004 cited by 639

  16. Softwarized Resource Management and Allocation With Autonomous Awareness for 6G-Enabled Cooperative Intelligent Transportation Systems

    Authors: Haotong Cao, Sahil Garg, Georges Kaddoum, Satinder Singh, M. Shamim Hossain - IEEE Transactions on Intelligent Transportation Systems, IEEE Trans. Intell. Transp. Syst. 2022 cited by 33

  17. Action-Conditional Video Prediction using Deep Networks in Atari Games

    Authors: Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh - http://www-personal.umich.edu/%7Erickl/pubs/oh-et-al-2015-NIPS.pdf 2015 cited by 909

  18. Diversifying AI: Towards Creative Chess with AlphaZero

    Authors: Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh - arXiv (Cornell University), CoRR 2023 cited by 16

  19. A Definition of Continual Reinforcement Learning

    Authors: David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado Philip van Hasselt, Satinder Singh - Advances in Neural Information Processing Systems 36, NeurIPS 2023 cited by 150

  20. Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality

    Authors: Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh - ICLR 2023 cited by 49

  21. Eligibility Traces for Off-Policy Policy Evaluation

    Authors: Doina Precup, Richard S. Sutton, Satinder Singh - ICML 2000 cited by 932

  22. Self-Imitation Learning

    Authors: Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee - International Conference on Machine Learning, ICML 2018 cited by 308

  23. Discovering Reinforcement Learning Algorithms

    Authors: Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver - Neural Information Processing Systems, NeurIPS 2020 cited by 150

  24. Code World Models for General Game Playing

    Authors: Wolfgang Lehrach, Daniel Hennes, Miguel Lázaro-Gredilla, Xinghua Lou, Carter Wendelken, Zun Li, Antoine Dedieu, Jordi Grau-Moya, Marc Lanctot, Atil Iscen, John Schultz, Marcus Chiam, Ian Gemp, Piotr Zielinski, Satinder Singh, Kevin P. Murphy - ArXiv.org, CoRR 2025 cited by 12