David Silver - RankMe

150 papers A* 50A 1Journal 79Unranked 20

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DataRater: Meta-Learned Dataset Curation. CoRR Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa M. Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeffrey Dean, Hado van Hasselt, David Silver
2025	J	`jnl`	Discovering state-of-the-art reinforcement learning algorithms. Nat. Junhyuk Oh, Gregory Farquhar, Iurii Kemaev, Dan A. Calian, Matteo Hessel, Luisa M. Zintgraf, Satinder Singh, Hado van Hasselt, David Silver
2023	J	`jnl`	Faster sorting algorithms discovered using deep reinforcement learning. Nat. Daniel J. Mankowitz, Andrea Michi, Anton Zhernov, Marco Gelmi, Marco Selvi, Cosmin Paduraru, Edouard Leurent, Shariq Iqbal, Jean-Baptiste Lespiau, Alex Ahern, Thomas Köppe, Kevin Millikin, Stephen Gaffney, Sophie Elster, Jackson Broshear, Chris Gamble, Kieran Milan, Robert Tung, Minjae Hwang, A. Taylan Cemgil, Mohammadamin Barekatain, Yujia Li, Amol Mandhane, Thomas Hubert, Julian Schrittwieser, Demis Hassabis, Pushmeet Kohli, Martin A. Riedmiller, Oriol Vinyals, David Silver
2022	A*	`conf`	Bootstrapped Meta-Learning. ICLR Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh
2022	J	`jnl`	Deep learning, reinforcement learning, and world models. Neural Networks Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto
2022	J	`jnl`	Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli
2022	A*	`conf`	Learning by Directional Gradient Descent. ICLR David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt
2022	J	`jnl`	Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR Julien Pérolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas W. Anthony, Stephen McAleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent Sifre, Nathalie Beauguerlange, Rémi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls
2022	A*	`conf`	Planning in Stochastic Environments with a Learned Model. ICLR Ioannis Antonoglou, Julian Schrittwieser, Sherjil Ozair, Thomas K. Hubert, David Silver
2022	A*	`conf`	Policy improvement by planning with Gumbel. ICLR Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver
2021	J	`jnl`	Bootstrapped Meta-Learning. CoRR Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh
2021	A*	`conf`	Discovery of Options via Meta-Learned Subgoals. NeurIPS Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
2021	J	`jnl`	Discovery of Options via Meta-Learned Subgoals. CoRR Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
2021	A*	`conf`	Expected Eligibility Traces. AAAI Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa
2021	A*	`conf`	Learning and Planning in Complex Action Spaces. ICML Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver
2021	J	`jnl`	Learning and Planning in Complex Action Spaces. CoRR Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver
2021	A*	`conf`	Muesli: Combining Improvements in Policy Optimization. ICML Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
2021	J	`jnl`	Muesli: Combining Improvements in Policy Optimization. CoRR Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
2021	A*	`conf`	Online and Offline Reinforcement Learning by Planning with a Learned Model. NeurIPS Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver
2021	J	`jnl`	Online and Offline Reinforcement Learning by Planning with a Learned Model. CoRR Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver
2021	A*	`conf`	Proper Value Equivalence. NeurIPS Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
2021	J	`jnl`	Proper Value Equivalence. CoRR Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
2021	J	`jnl`	Reward is enough. Artif. Intell. David Silver, Satinder Singh, Doina Precup, Richard S. Sutton
2021	A*	`conf`	Self-Consistent Models and Values. NeurIPS Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado Philip van Hasselt, David Silver
2021	J	`jnl`	Self-Consistent Models and Values. CoRR Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado van Hasselt, David Silver
2021	J	`jnl`	The Option Keyboard: Combining Skills in Reinforcement Learning. CoRR André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup
2021	A*	`conf`	The Value-Improvement Path: Towards Better Representations for Reinforcement Learning. AAAI Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
2020	A*	`conf`	A Self-Tuning Actor-Critic Algorithm. NeurIPS Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2020	A*	`conf`	Behaviour Suite for Reinforcement Learning. ICLR 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
2020	A*	`conf`	Discovering Reinforcement Learning Algorithms. NeurIPS Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
2020	J	`jnl`	Discovering Reinforcement Learning Algorithms. CoRR Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
2020	J	`jnl`	Expected Eligibility Traces. CoRR Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa
2020	J	`jnl`	Fast reinforcement learning with generalized policy updates. Proc. Natl. Acad. Sci. USA André Barreto, Shaobo Hou, Diana Borsa, David Silver, Doina Precup
2020	J	`jnl`	Improved protein structure prediction using potentials from deep learning. Nat. Andrew W. Senior, Richard Evans, John Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Zídek, Alexander W. R. Nelson, Alex Bridgland, Hugo Penedones, Stig Petersen, Karen Simonyan, Steve Crossan, Pushmeet Kohli, David T. Jones, David Silver, Koray Kavukcuoglu, Demis Hassabis
2020	J	`jnl`	Mastering Atari, Go, chess and shogi by planning with a learned model. Nat. Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver
2020	A*	`conf`	Meta-Gradient Reinforcement Learning with an Objective Discovered Online. NeurIPS Zhongwen Xu, Hado Philip van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
2020	J	`jnl`	Meta-Gradient Reinforcement Learning with an Objective Discovered Online. CoRR Zhongwen Xu, Hado van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
2020	J	`jnl`	Self-Tuning Deep Reinforcement Learning. CoRR Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2020	A*	`conf`	The Value Equivalence Principle for Model-Based Reinforcement Learning. NeurIPS Christopher Grimm, André Barreto, Satinder Singh, David Silver
2020	J	`jnl`	The Value Equivalence Principle for Model-Based Reinforcement Learning. CoRR Christopher Grimm, André Barreto, Satinder Singh, David Silver
2020	J	`jnl`	The Value-Improvement Path: Towards Better Representations for Reinforcement Learning. CoRR Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
2020	A*	`conf`	Value-driven Hindsight Modelling. NeurIPS Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess
2020	J	`jnl`	Value-driven Hindsight Modelling. CoRR Arthur Guez, Fabio Viola, Théophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess
2020	A*	`conf`	What Can Learned Intrinsic Rewards Capture? ICML Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
2019	A*	`conf`	An Investigation of Model-Free Planning. ICML Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap
2019	J	`jnl`	An investigation of model-free planning. CoRR Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Théophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap
2019	J	`jnl`	Behaviour Suite for Reinforcement Learning. CoRR 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
2019	A	`conf`	Credit Assignment Techniques in Stochastic Computation Graphs. AISTATS Théophane Weber, Nicolas Heess, Lars Buesing, David Silver
2019	J	`jnl`	Credit Assignment Techniques in Stochastic Computation Graphs. CoRR Théophane Weber, Nicolas Heess, Lars Buesing, David Silver
2019	A*	`conf`	Discovery of Useful Questions as Auxiliary Tasks. NeurIPS Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2019	J	`jnl`	Discovery of Useful Questions as Auxiliary Tasks. CoRR Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard L. Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2019	J	`jnl`	Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver
2019	J	`jnl`	Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model. CoRR Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver
2019	J	`jnl`	On Inductive Biases in Deep Reinforcement Learning. CoRR Matteo Hessel, Hado van Hasselt, Joseph Modayil, David Silver
2019	A*	`conf`	The Option Keyboard: Combining Skills in Reinforcement Learning. NeurIPS André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup
2019	J	`jnl`	Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. CoRR André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
2019	—	`conf`	Universal Successor Features Approximators. ICLR (Poster) Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Rémi Munos, David Silver, Tom Schaul
2019	J	`jnl`	What Can Learned Intrinsic Rewards Capture? CoRR Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
2018	J	`jnl`	Bayesian Optimization in AlphaGo. CoRR Yutian Chen, Aja Huang, Ziyu Wang, Ioannis Antonoglou, Julian Schrittwieser, David Silver, Nando de Freitas
2018	—	`conf`	Distributed Prioritized Experience Replay. ICLR (Poster) Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver
2018	J	`jnl`	Distributed Prioritized Experience Replay. CoRR Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver
2018	J	`jnl`	Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. CoRR Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel
2018	A*	`conf`	Implicit Quantile Networks for Distributional Reinforcement Learning. ICML Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
2018	J	`jnl`	Implicit Quantile Networks for Distributional Reinforcement Learning. CoRR Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
2018	J	`jnl`	Introduction to the special issue on deep reinforcement learning: An editorial. Neural Networks Ron Sun, David Silver, Gerald Tesauro, Guang-Bin Huang
2018	A*	`conf`	Learning to Search with MCTSnets. ICML Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
2018	J	`jnl`	Learning to Search with MCTSnets. CoRR Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
2018	A*	`conf`	Meta-Gradient Reinforcement Learning. NeurIPS Zhongwen Xu, Hado van Hasselt, David Silver
2018	J	`jnl`	Meta-Gradient Reinforcement Learning. CoRR Zhongwen Xu, Hado van Hasselt, David Silver
2018	A*	`conf`	Rainbow: Combining Improvements in Deep Reinforcement Learning. AAAI Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
2018	A*	`conf`	Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. ICML André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
2018	J	`jnl`	Unicorn: Continual Learning with a Universal, Off-policy Agent. CoRR Daniel J. Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul
2018	J	`jnl`	Universal Successor Features Approximators. CoRR Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Rémi Munos, Hado van Hasselt, David Silver, Tom Schaul
2018	J	`jnl`	Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack W. Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Jimenez Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matthew M. Botvinick, Demis Hassabis, Timothy P. Lillicrap
2017	—	`conf`	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
2017	J	`jnl`	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
2017	A*	`conf`	Decoupled Neural Interfaces using Synthetic Gradients. ICML Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, David Silver, Koray Kavukcuoglu
2017	J	`jnl`	Emergence of Locomotion Behaviours in Rich Environments. CoRR Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin A. Riedmiller, David Silver
2017	A*	`conf`	FeUdal Networks for Hierarchical Reinforcement Learning. ICML Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu
2017	J	`jnl`	FeUdal Networks for Hierarchical Reinforcement Learning. CoRR Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu
2017	—	`conf`	Imagination-Augmented Agents for Deep Reinforcement Learning. NIPS Sébastien Racanière, Theophane Weber, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, Demis Hassabis, David Silver, Daan Wierstra
2017	J	`jnl`	Imagination-Augmented Agents for Deep Reinforcement Learning. CoRR Theophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, David Silver, Daan Wierstra
2017	J	`jnl`	Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. CoRR David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, Demis Hassabis
2017	J	`jnl`	Mastering the game of Go without human knowledge. Nat. David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy P. Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis
2017	—	`conf`	Natural Value Approximators: Learning when to Trust Past Estimates. NIPS Zhongwen Xu, Joseph Modayil, Hado van Hasselt, André Barreto, David Silver, Tom Schaul
2017	J	`jnl`	Rainbow: Combining Improvements in Deep Reinforcement Learning. CoRR Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Daniel Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
2017	—	`conf`	Reinforcement Learning with Unsupervised Auxiliary Tasks. ICLR Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
2017	J	`jnl`	StarCraft II: A New Challenge for Reinforcement Learning. CoRR Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John P. Agapiou, Julian Schrittwieser, John Quan, Stephen Gaffney, Stig Petersen, Karen Simonyan, Tom Schaul, Hado van Hasselt, David Silver, Timothy P. Lillicrap, Kevin Calderone, Paul Keet, Anthony Brunasso, David Lawrence, Anders Ekermo, Jacob Repp, Rodney Tsing
2017	—	`conf`	Successor Features for Transfer in Reinforcement Learning. NIPS André Barreto, Will Dabney, Rémi Munos, Jonathan J. Hunt, Tom Schaul, David Silver, Hado van Hasselt
2017	J	`jnl`	Technical perspective: Solving imperfect information games. Commun. ACM David Silver
2017	A*	`conf`	The Predictron: End-To-End Learning and Planning. ICML David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris
2016	A*	`conf`	Asynchronous Methods for Deep Reinforcement Learning. ICML Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
2016	J	`jnl`	Asynchronous Methods for Deep Reinforcement Learning. CoRR Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
2016	A*	`conf`	Continuous control with deep reinforcement learning. ICLR (Poster) Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra
2016	J	`jnl`	Deep Reinforcement Learning from Self-Play in Imperfect-Information Games. CoRR Johannes Heinrich, David Silver
2016	A*	`conf`	Deep Reinforcement Learning with Double Q-Learning. AAAI Hado van Hasselt, Arthur Guez, David Silver
2016	J	`jnl`	Learning and Transfer of Modulated Locomotor Controllers. CoRR Nicolas Heess, Gregory Wayne, Yuval Tassa, Timothy P. Lillicrap, Martin A. Riedmiller, David Silver
2016	J	`jnl`	Learning functions across many orders of magnitudes. CoRR Hado van Hasselt, Arthur Guez, Matteo Hessel, David Silver
2016	—	`conf`	Learning values across many orders of magnitude. NIPS Hado van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver
2016	J	`jnl`	Mastering the game of Go with deep neural networks and tree search. Nat. David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy P. Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis
2016	A*	`conf`	Prioritized Experience Replay. ICLR (Poster) Tom Schaul, John Quan, Ioannis Antonoglou, David Silver
2016	J	`jnl`	Reinforcement Learning with Unsupervised Auxiliary Tasks. CoRR Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
2016	J	`jnl`	Successor Features for Transfer in Reinforcement Learning. CoRR André Barreto, Rémi Munos, Tom Schaul, David Silver
2016	J	`jnl`	The Predictron: End-To-End Learning and Planning. CoRR David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris
2015	J	`jnl`	Deep Reinforcement Learning with Double Q-learning. CoRR Hado van Hasselt, Arthur Guez, David Silver
2015	A*	`conf`	Fictitious Self-Play in Extensive-Form Games. ICML Johannes Heinrich, Marc Lanctot, David Silver
2015	J	`jnl`	Human-level control through deep reinforcement learning. Nat. Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis
2015	—	`conf`	Learning Continuous Control Policies by Stochastic Value Gradients. NIPS Nicolas Heess, Gregory Wayne, David Silver, Timothy P. Lillicrap, Tom Erez, Yuval Tassa
2015	J	`jnl`	Learning Continuous Control Policies by Stochastic Value Gradients. CoRR Nicolas Heess, Greg Wayne, David Silver, Timothy P. Lillicrap, Yuval Tassa, Tom Erez
2015	J	`jnl`	Massively Parallel Methods for Deep Reinforcement Learning. CoRR Arun Nair, Praveen Srinivasan, Sam Blackwell, Cagdas Alcicek, Rory Fearon, Alessandro De Maria, Vedavyas Panneershelvam, Mustafa Suleyman, Charles Beattie, Stig Petersen, Shane Legg, Volodymyr Mnih, Koray Kavukcuoglu, David Silver
2015	J	`jnl`	Memory-based control with recurrent neural networks. CoRR Nicolas Heess, Jonathan J. Hunt, Timothy P. Lillicrap, David Silver
2015	—	`conf`	Move Evaluation in Go Using Deep Convolutional Neural Networks. ICLR (Poster) Chris J. Maddison, Aja Huang, Ilya Sutskever, David Silver
2015	A*	`conf`	Smooth UCT Search in Computer Poker. IJCAI Johannes Heinrich, David Silver
2015	A*	`conf`	Universal Value Function Approximators. ICML Tom Schaul, Daniel Horgan, Karol Gregor, David Silver
2015	J	`jnl`	Value Iteration with Options and State Aggregation. CoRR Kamil Ciosek, David Silver
2014	—	`conf`	Bayes-Adaptive Simulation-based Search with Value Function Approximation. NIPS Arthur Guez, Nicolas Heess, David Silver, Peter Dayan
2014	J	`jnl`	Better Optimism By Bayes: Adaptive Planning with Rich Models. CoRR Arthur Guez, David Silver, Peter Dayan
2014	A*	`conf`	Deterministic Policy Gradient Algorithms. ICML David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller
2014	J	`jnl`	Learning to Win by Reading Manuals in a Monte-Carlo Framework. CoRR S. R. K. Branavan, David Silver, Regina Barzilay
2014	—	`conf`	Unit Tests for Stochastic Optimization. ICLR Tom Schaul, Ioannis Antonoglou, David Silver
2013	—	`conf`	Concurrent Reinforcement Learning from Customer Interactions. ICML (3) David Silver, Leonard Newnham, David Barker, Suzanne Weller, Jason McFall
2013	J	`jnl`	Playing Atari with Deep Reinforcement Learning. CoRR Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin A. Riedmiller
2013	J	`jnl`	Scalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search. J. Artif. Intell. Res. Arthur Guez, David Silver, Peter Dayan
2013	A*	`conf`	Temporal-Difference Search in Computer Go. ICAPS David Silver, Richard S. Sutton, Martin Müller
2012	—	`conf`	Actor-Critic Reinforcement Learning with Energy-Based Policies. EWRL Nicolas Heess, David Silver, Yee Whye Teh
2012	A*	`conf`	Compositional Planning Using Optimal Option Models. ICML David Silver, Kamil Ciosek
2012	J	`jnl`	Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search CoRR Arthur Guez, David Silver, Peter Dayan
2012	—	`conf`	Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. NIPS Arthur Guez, David Silver, Peter Dayan
2012	—	`conf`	Gradient Temporal Difference Networks. EWRL David Silver
2012	J	`jnl`	Learning to Win by Reading Manuals in a Monte-Carlo Framework. J. Artif. Intell. Res. S. R. K. Branavan, David Silver, Regina Barzilay
2012	J	`jnl`	Temporal-difference search in computer Go. Mach. Learn. David Silver, Richard S. Sutton, Martin Müller
2012	J	`jnl`	The grand challenge of computer Go: Monte Carlo tree search and extensions. Commun. ACM Sylvain Gelly, Levente Kocsis, Marc Schoenauer, Michèle Sebag, David Silver, Csaba Szepesvári, Olivier Teytaud
2011	J	`jnl`	A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver
2011	A*	`conf`	Learning to Win by Reading Manuals in a Monte-Carlo Framework. ACL S. R. K. Branavan, David Silver, Regina Barzilay
2011	J	`jnl`	Monte-Carlo tree search and rapid action value estimation in computer Go. Artif. Intell. Sylvain Gelly, David Silver
2011	A*	`conf`	Non-Linear Monte-Carlo Search in Civilization II. IJCAI S. R. K. Branavan, David Silver, Regina Barzilay
2010	—	`conf`	Monte-Carlo Planning in Large POMDPs. NIPS David Silver, Joel Veness
2010	J	`jnl`	Reinforcement Learning via AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2010	A*	`conf`	Reinforcement Learning via AIXI Approximation. AAAI Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	J	`jnl`	A Monte Carlo AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	—	`conf`	Bootstrapping from Game Tree Search. NIPS Joel Veness, David Silver, William T. B. Uther, Alan Blair
2009	—	`conf`	Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation. NIPS Hamid Reza Maei, Csaba Szepesvári, Shalabh Bhatnagar, Doina Precup, David Silver, Richard S. Sutton
2009	A*	`conf`	Fast gradient-descent methods for temporal-difference learning with linear function approximation. ICML Richard S. Sutton, Hamid Reza Maei, Doina Precup, Shalabh Bhatnagar, David Silver, Csaba Szepesvári, Eric Wiewiora
2009	A*	`conf`	Monte-Carlo simulation balancing. ICML David Silver, Gerald Tesauro
2008	A*	`conf`	Achieving Master Level Play in 9 x 9 Computer Go. AAAI Sylvain Gelly, David Silver
2008	A*	`conf`	Sample-based learning and search with permanent and transient memories. ICML David Silver, Richard S. Sutton, Martin Müller
2007	A*	`conf`	Combining online and offline knowledge in UCT. ICML Sylvain Gelly, David Silver
2007	A*	`conf`	On the role of tracking in stationary environments. ICML Richard S. Sutton, Anna Koop, David Silver
2007	A*	`conf`	Reinforcement Learning of Local Shape in the Game of Go. IJCAI David Silver, Richard S. Sutton, Martin Müller
2005	—	`conf`	Cooperative Pathfinding. AIIDE David Silver