van Hasselt, Hado P

16 publications

NeurIPS 2023 A Definition of Continual Reinforcement Learning David Abel, Andre Barreto, Benjamin Van Roy, Doina Precup, Hado P van Hasselt, Satinder P. Singh

NeurIPS 2023 Optimistic Meta-Gradients Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado P van Hasselt, András György, Satinder P. Singh

NeurIPS 2021 Discovery of Options via Meta-Learned Subgoals Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado P van Hasselt, David Silver, Satinder P. Singh

NeurIPS 2021 Self-Consistent Models and Values Greg Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado P van Hasselt, David Silver

NeurIPS 2020 A Self-Tuning Actor-Critic Algorithm Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder P. Singh

NeurIPS 2020 Discovering Reinforcement Learning Algorithms Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado P van Hasselt, Satinder P. Singh, David Silver

NeurIPS 2020 Forethought and Hindsight in Credit Assignment Veronica Chelu, Doina Precup, Hado P van Hasselt

NeurIPS 2020 Meta-Gradient Reinforcement Learning with an Objective Discovered Online Zhongwen Xu, Hado P van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder P. Singh, David Silver

NeurIPS 2019 Discovery of Useful Questions as Auxiliary Tasks Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder Singh

NeurIPS 2019 Hindsight Credit Assignment Anna Harutyunyan, Will Dabney, Thomas Mesnard, Mohammad Gheshlaghi Azar, Bilal Piot, Nicolas Heess, Hado P van Hasselt, Gregory Wayne, Satinder Singh, Doina Precup, Remi Munos

NeurIPS 2019 When to Use Parametric Models in Reinforcement Learning? Hado P van Hasselt, Matteo Hessel, John Aslanides

NeurIPS 2018 Meta-Gradient Reinforcement Learning Zhongwen Xu, Hado P van Hasselt, David Silver

NeurIPS 2017 Natural Value Approximators: Learning When to Trust past Estimates Zhongwen Xu, Joseph Modayil, Hado P van Hasselt, Andre Barreto, David Silver, Tom Schaul

NeurIPS 2017 Successor Features for Transfer in Reinforcement Learning Andre Barreto, Will Dabney, Remi Munos, Jonathan J Hunt, Tom Schaul, Hado P van Hasselt, David Silver

NeurIPS 2016 Learning Values Across Many Orders of Magnitude Hado P van Hasselt, Arthur Guez, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver

NeurIPS 2014 Weighted Importance Sampling for Off-Policy Learning with Linear Function Approximation A. Rupam Mahmood, Hado P van Hasselt, Richard S. Sutton