HH
Hado van Hasselt
cs.LGcs.AIstat.MLcs.NEAlgorithmsReinforcement, PsychologyArtificial IntelligenceMachine Learningmath.OCModels, Theoretical
On Valency
published · living versionsW_z8p2yx7z·v1 · currentpublished
Dueling Network Architectures for Deep Reinforcement Learning
with Ziyu Wang, Tom Schaul, Matteo Hessel, Marc Lanctot +1
1 version
Preprints & journals
59 papers in the corpus · 2008–2025Discovering state-of-the-art reinforcement learning algorithms.41125136 · Oh, Junhyuk, Farquhar, Gregory, Kemaev, Iurii et al.2025 · 17 citationsNature. 2025;648(8093):312-319
DataRater: Meta-Learned Dataset Curation2505.17895v2 · Dan A. Calian, Gregory Farquhar, Iurii Kemaev et al.2025 · 1 citationarXiv
Wasserstein Policy Optimization2505.00663v1 · David Pfau, Ian Davies, Diana Borsa et al.2025 · 0 citationsarXiv
Scalable Meta-Learning via Mixed-Mode Differentiation2505.00793v2 · Iurii Kemaev, Dan A Calian, Luisa M Zintgraf et al.2025 · 0 citationsarXiv
General Uncertainty Estimation with Delta Variances2502.14698v2 · Simon Schmitt, John Shawe-Taylor, Hado van Hasselt2025 · 1 citationarXiv
Normalization and effective learning rates in reinforcement learning2407.01800v1 · Clare Lyle, Zeyu Zheng, Khimya Khetarpal et al.2024 · 4 citationsarXiv
Disentangling the Causes of Plasticity Loss in Neural Networks2402.18762v1 · Clare Lyle, Zeyu Zheng, Khimya Khetarpal et al.2024 · 5 citationsarXiv
A Survey of Temporal Credit Assignment in Deep Reinforcement Learning2312.01072v2 · Eduardo Pignatelli, Johan Ferret, Matthieu Geist et al.2023 · 2 citationsarXiv
On the Convergence of Bounded Agents2307.11044v1 · David Abel, Andr'e Barreto, Hado van Hasselt et al.2023 · 0 citationsarXiv
A Definition of Continual Reinforcement Learning2307.11046v2 · David Abel, Andr'e Barreto, Benjamin Van Roy et al.2023 · 36 citationsarXiv
Exploration via Epistemic Value Estimation2303.04012v1 · Simon Schmitt, John Shawe-Taylor, Hado van Hasselt2023 · 3 citationsarXiv
Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration2302.04250v2 · Chentian Jiang, Nan Rosemary Ke, Hado van Hasselt2023 · 1 citationarXiv
Optimistic Meta-Gradients2301.03236v1 · Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue et al.2023 · 0 citationsarXiv
Human-level Atari 200x faster2209.07550v1 · Steven Kapturowski, V'ictor Campos, Ray Jiang et al.2022 · 4 citationsarXiv
Selective Credit Assignment2202.09699v1 · Veronica Chelu, Diana Borsa, Doina Precup et al.2022 · 1 citationarXiv
Chaining Value Functions for Off-Policy Learning2201.06468v2 · Simon Schmitt, John Shawe-Taylor, Hado van Hasselt2022 · 2 citationsarXiv
Self-Consistent Models and Values2110.12840v1 · Gregory Farquhar, Kate Baumli, Zita Marinho et al.2021 · 2 citationsarXiv
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity2110.04041v1 · Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu et al.2021 · 3 citationsarXiv
Introducing Symmetries to Black Box Meta Reinforcement Learning2109.10781v2 · Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt et al.2021 · 16 citationsarXiv
Bootstrapped Meta-Learning2109.04504v2 · Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy et al.2021 · 9 citationsarXiv
Learning Expected Emphatic Traces for Deep RL2107.05405v1 · Ray Jiang, Shangtong Zhang, Veronica Chelu et al.2021 · 6 citationsarXiv
Emphatic Algorithms for Deep Reinforcement Learning2106.11779v1 · Ray Jiang, Tom Zahavy, Zhongwen Xu et al.2021 · 7 citationsProceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021
Muesli: Combining Improvements in Policy Optimization2104.06159v2 · Matteo Hessel, Ivo Danihelka, Fabio Viola et al.2021 · 18 citationsarXiv
Podracer architectures for scalable Reinforcement Learning2104.06272v1 · Matteo Hessel, Manuel Kroiss, Aidan Clark et al.2021 · 8 citationsarXiv
Synthetic Returns for Long-Term Credit Assignment2102.12425v1 · David Raposo, Sam Ritter, Adam Santoro et al.2021 · 11 citationsarXiv
Discovery of Options via Meta-Learned Subgoals2102.06741v1 · Vivek Veeriah, Tom Zahavy, Matteo Hessel et al.2021 · 8 citationsarXiv
Forethought and Hindsight in Credit Assignment2010.13685v1 · Veronica Chelu, Doina Precup, Hado van Hasselt2020 · 13 citationsarXiv
Discovering Reinforcement Learning Algorithms2007.08794v3 · Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki et al.2020 · 71 citationsarXiv
Meta-Gradient Reinforcement Learning with an Objective Discovered Online2007.08433v1 · Zhongwen Xu, Hado van Hasselt, Matteo Hessel et al.2020 · 41 citationsarXiv
Expected Eligibility Traces2007.01839v2 · Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel et al.2020 · 2 citationsarXiv
A Self-Tuning Actor-Critic Algorithm2002.12928v5 · Tom Zahavy, Zhongwen Xu, Vivek Veeriah et al.2020 · 46 citationsarXiv
What Can Learned Intrinsic Rewards Capture?1912.05500v3 · Zeyu Zheng, Junhyuk Oh, Matteo Hessel et al.2019 · 43 citationsarXiv
Hindsight Credit Assignment1912.02503v1 · Anna Harutyunyan, Will Dabney, Thomas Mesnard et al.2019 · 42 citationsarXiv
Conditional Importance Sampling for Off-Policy Learning1910.07479v2 · Mark Rowland, Anna Harutyunyan, Hado van Hasselt et al.2019 · 3 citationsarXiv
Discovery of Useful Questions as Auxiliary Tasks1909.04607v1 · Vivek Veeriah, Matteo Hessel, Zhongwen Xu et al.2019 · 45 citationsarXiv
Behaviour Suite for Reinforcement Learning1908.03568v3 · Ian Osband, Yotam Doron, Matteo Hessel et al.2019 · 58 citationsarXiv
General non-linear Bellman equations1907.03687v1 · Hado van Hasselt, John Quan, Matteo Hessel et al.2019 · 9 citationsarXiv
On Inductive Biases in Deep Reinforcement Learning1907.02908v1 · Matteo Hessel, Hado van Hasselt, Joseph Modayil et al.2019 · 20 citationsarXiv
When to use parametric models in reinforcement learning?1906.05243v1 · Hado van Hasselt, Matteo Hessel, John Aslanides2019 · 99 citationsNeurIPS 2019
Meta-learning of Sequential Strategies1905.03030v2 · Pedro A. Ortega, Jane X. Wang, Mark Rowland et al.2019 · 47 citationsarXiv
Universal Successor Features Approximators1812.07626v1 · Diana Borsa, Andr'e Barreto, John Quan et al.2018 · 41 citationsarXiv
Deep Reinforcement Learning and the Deadly Triad1812.02648v1 · Hado van Hasselt, Yotam Doron, Florian Strub et al.2018 · 101 citationsarXiv
The Barbados 2018 List of Open Issues in Continual Learning1811.07004v1 · Tom Schaul, Hado van Hasselt, Joseph Modayil et al.2018 · 4 citationsarXiv
Multi-task Deep Reinforcement Learning with PopArt1809.04474v1 · Matteo Hessel, Hubert Soyer, Lasse Espeholt et al.2018 · 233 citationsarXiv
Observe and Look Further: Achieving Consistent Performance on Atari1805.11593v1 · Tobias Pohlen, Bilal Piot, Todd Hester et al.2018 · 80 citationsarXiv
Meta-Gradient Reinforcement Learning1805.09801v1 · Zhongwen Xu, Hado van Hasselt, David Silver2018 · 198 citationsarXiv
Distributed Prioritized Experience Replay1803.00933v1 · Dan Horgan, John Quan, David Budden et al.2018 · 555 citationsarXiv
Unicorn: Continual Learning with a Universal, Off-policy Agent1802.08294v2 · Daniel J. Mankowitz, Augustin Z'idek, Andr'e Barreto et al.2018 · 35 citationsarXiv
Rainbow: Combining Improvements in Deep Reinforcement Learning1710.02298v1 · Matteo Hessel, Joseph Modayil, Hado van Hasselt et al.2017 · 2,050 citationsarXiv
StarCraft II: A New Challenge for Reinforcement Learning1708.04782v1 · Oriol Vinyals, Timo Ewalds, Sergey Bartunov et al.2017 · 678 citationsarXiv
Career total: 105 works. 59 are in this corpus.Showing the 50 most recent.
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