David Silver

ORCID

Publication Activity (10 Years)

Years Active: 2000-2023
Publications (10 Years): 103

Top Venues

Publications

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, Taylan Cemgil, Mohammadamin Barekatain, Yujia Li, Amol Mandhane, Thomas Hubert, Julian Schrittwieser, Demis Hassabis, Pushmeet Kohli, Martin A. Riedmiller, Oriol Vinyals, David Silver
Faster sorting algorithms discovered using deep reinforcement learning. Nat. 618 (7964) (2023)
Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy P. Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul Ronald Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, et al.
Gemini: A Family of Highly Capable Multimodal Models. CoRR (2023)
Ioannis Antonoglou, Julian Schrittwieser, Sherjil Ozair, Thomas K. Hubert, David Silver
Planning in Stochastic Environments with a Learned Model. ICLR (2022)
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
Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. 610 (7930) (2022)
Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh
Bootstrapped Meta-Learning. ICLR (2022)
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
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR (2022)
David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt
Learning by Directional Gradient Descent. ICLR (2022)
Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto
Deep learning, reinforcement learning, and world models. Neural Networks 152 (2022)
Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver
Policy improvement by planning with Gumbel. ICLR (2022)
Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
Proper Value Equivalence. NeurIPS (2021)
Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa
Expected Eligibility Traces. AAAI (2021)
Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning. AAAI (2021)
David Silver, Satinder P. Singh, Doina Precup, Richard S. Sutton
Reward is enough. Artif. Intell. 299 (2021)
André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup
The Option Keyboard: Combining Skills in Reinforcement Learning. CoRR (2021)
Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver
Learning and Planning in Complex Action Spaces. CoRR (2021)
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
Muesli: Combining Improvements in Policy Optimization. ICML (2021)
Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado van Hasselt, David Silver
Self-Consistent Models and Values. CoRR (2021)
Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver
Learning and Planning in Complex Action Spaces. ICML (2021)
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt
Muesli: Combining Improvements in Policy Optimization. CoRR (2021)
Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
Discovery of Options via Meta-Learned Subgoals. CoRR (2021)
Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
Proper Value Equivalence. CoRR (2021)
Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver
Online and Offline Reinforcement Learning by Planning with a Learned Model. NeurIPS (2021)
Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver
Online and Offline Reinforcement Learning by Planning with a Learned Model. CoRR (2021)
Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
Discovery of Options via Meta-Learned Subgoals. NeurIPS (2021)
Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado Philip van Hasselt, David Silver
Self-Consistent Models and Values. NeurIPS (2021)
Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh
Bootstrapped Meta-Learning. CoRR (2021)
Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
Discovering Reinforcement Learning Algorithms. CoRR (2020)
Arthur Guez, Fabio Viola, Théophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess
Value-driven Hindsight Modelling. CoRR (2020)
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
Improved protein structure prediction using potentials from deep learning. Nat. 577 (7792) (2020)
Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
A Self-Tuning Actor-Critic Algorithm. NeurIPS (2020)
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
Behaviour Suite for Reinforcement Learning. ICLR (2020)
Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
What Can Learned Intrinsic Rewards Capture? ICML (2020)
Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning. CoRR (2020)
Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess
Value-driven Hindsight Modelling. NeurIPS (2020)
Christopher Grimm, André Barreto, Satinder Singh, David Silver
The Value Equivalence Principle for Model-Based Reinforcement Learning. CoRR (2020)
André Barreto, Shaobo Hou, Diana Borsa, David Silver, Doina Precup
Fast reinforcement learning with generalized policy updates. Proc. Natl. Acad. Sci. USA 117 (48) (2020)
Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
Discovering Reinforcement Learning Algorithms. NeurIPS (2020)
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
Mastering Atari, Go, chess and shogi by planning with a learned model. Nat. 588 (7839) (2020)
Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa
Expected Eligibility Traces. CoRR (2020)
Zhongwen Xu, Hado Philip van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
Meta-Gradient Reinforcement Learning with an Objective Discovered Online. NeurIPS (2020)
Zhongwen Xu, Hado van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
Meta-Gradient Reinforcement Learning with an Objective Discovered Online. CoRR (2020)
Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
Self-Tuning Deep Reinforcement Learning. CoRR (2020)
Christopher Grimm, André Barreto, Satinder Singh, David Silver
The Value Equivalence Principle for Model-Based Reinforcement Learning. NeurIPS (2020)
Matteo Hessel, Hado van Hasselt, Joseph Modayil, David Silver
On Inductive Biases in Deep Reinforcement Learning. CoRR (2019)
Théophane Weber, Nicolas Heess, Lars Buesing, David Silver
Credit Assignment Techniques in Stochastic Computation Graphs. CoRR (2019)
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
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model. CoRR (2019)
Théophane Weber, Nicolas Heess, Lars Buesing, David Silver
Credit Assignment Techniques in Stochastic Computation Graphs. AISTATS (2019)
André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup
The Option Keyboard: Combining Skills in Reinforcement Learning. NeurIPS (2019)
Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
Discovery of Useful Questions as Auxiliary Tasks. NeurIPS (2019)
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
An investigation of model-free planning. CoRR (2019)
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
Behaviour Suite for Reinforcement Learning. CoRR (2019)
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
An Investigation of Model-Free Planning. ICML (2019)
Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard L. Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
Discovery of Useful Questions as Auxiliary Tasks. CoRR (2019)
Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
What Can Learned Intrinsic Rewards Capture? CoRR (2019)
André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. CoRR (2019)
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
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575 (7782) (2019)
Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Rémi Munos, David Silver, Tom Schaul
Universal Successor Features Approximators. ICLR (Poster) (2019)
Zhongwen Xu, Hado van Hasselt, David Silver
Meta-Gradient Reinforcement Learning. CoRR (2018)
Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Rémi Munos, Hado van Hasselt, David Silver, Tom Schaul
Universal Successor Features Approximators. CoRR (2018)
Daniel J. Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul
Unicorn: Continual Learning with a Universal, Off-policy Agent. CoRR (2018)
Zhongwen Xu, Hado van Hasselt, David Silver
Meta-Gradient Reinforcement Learning. NeurIPS (2018)
Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
Implicit Quantile Networks for Distributional Reinforcement Learning. CoRR (2018)
Yutian Chen, Aja Huang, Ziyu Wang, Ioannis Antonoglou, Julian Schrittwieser, David Silver, Nando de Freitas
Bayesian Optimization in AlphaGo. CoRR (2018)
Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
Learning to Search with MCTSnets. ICML (2018)
Ron Sun, David Silver, Gerald Tesauro, Guang-Bin Huang
Introduction to the special issue on deep reinforcement learning: An editorial. Neural Networks 107 (2018)
Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver
Distributed Prioritized Experience Replay. ICLR (Poster) (2018)
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
Rainbow: Combining Improvements in Deep Reinforcement Learning. AAAI (2018)
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 Botvinick, Demis Hassabis, Timothy P. Lillicrap
Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR (2018)
André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. ICML (2018)
Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver
Distributed Prioritized Experience Replay. CoRR (2018)
Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
Learning to Search with MCTSnets. CoRR (2018)
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
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. CoRR (2018)
Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
Implicit Quantile Networks for Distributional Reinforcement Learning. ICML (2018)
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
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. CoRR (2017)
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
Emergence of Locomotion Behaviours in Rich Environments. CoRR (2017)
Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, David Silver, Koray Kavukcuoglu
Decoupled Neural Interfaces using Synthetic Gradients. ICML (2017)
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
Imagination-Augmented Agents for Deep Reinforcement Learning. NIPS (2017)
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
StarCraft II: A New Challenge for Reinforcement Learning. CoRR (2017)
André Barreto, Will Dabney, Rémi Munos, Jonathan J. Hunt, Tom Schaul, David Silver, Hado van Hasselt
Successor Features for Transfer in Reinforcement Learning. NIPS (2017)
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
Imagination-Augmented Agents for Deep Reinforcement Learning. CoRR (2017)
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu
FeUdal Networks for Hierarchical Reinforcement Learning. ICML (2017)
Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR (2017)
Zhongwen Xu, Joseph Modayil, Hado van Hasselt, André Barreto, David Silver, Tom Schaul
Natural Value Approximators: Learning when to Trust Past Estimates. NIPS (2017)
David Silver
Technical perspective: Solving imperfect information games. Commun. ACM 60 (11) (2017)
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
Mastering the game of Go without human knowledge. Nat. 550 (7676) (2017)
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
The Predictron: End-To-End Learning and Planning. ICML (2017)
Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS (2017)
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
Reinforcement Learning with Unsupervised Auxiliary Tasks. ICLR (2017)
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu
FeUdal Networks for Hierarchical Reinforcement Learning. CoRR (2017)
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Daniel Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
Rainbow: Combining Improvements in Deep Reinforcement Learning. CoRR (2017)
Johannes Heinrich, David Silver
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games. CoRR (2016)
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
Mastering the game of Go with deep neural networks and tree search. Nat. 529 (7587) (2016)
Hado van Hasselt, Arthur Guez, Matteo Hessel, David Silver
Learning functions across many orders of magnitudes. CoRR (2016)
Nicolas Heess, Gregory Wayne, Yuval Tassa, Timothy P. Lillicrap, Martin A. Riedmiller, David Silver
Learning and Transfer of Modulated Locomotor Controllers. CoRR (2016)
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
Asynchronous Methods for Deep Reinforcement Learning. CoRR (2016)
Hado van Hasselt, Arthur Guez, David Silver
Deep Reinforcement Learning with Double Q-Learning. AAAI (2016)
André Barreto, Rémi Munos, Tom Schaul, David Silver
Successor Features for Transfer in Reinforcement Learning. CoRR (2016)
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra
Continuous control with deep reinforcement learning. ICLR (Poster) (2016)
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
The Predictron: End-To-End Learning and Planning. CoRR (2016)
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
Reinforcement Learning with Unsupervised Auxiliary Tasks. CoRR (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

David Silver