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2020 – today
- 2024
[j5]Tuomas Haarnoja
, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess:
Learning agile soccer skills for a bipedal robot with deep reinforcement learning. Sci. Robotics 9(89) (2024)- [c19]Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti:
Generative Adversarial Equilibrium Solvers. ICLR 2024 - [c18]Dhruva Tirumala, Thomas Lampe, José Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier:
Replay across Experiments: A Natural Extension of Off-Policy RL. ICLR 2024 - [i16]Dhruva Tirumala, Markus Wulfmeier, Ben Moran, Sandy H. Huang, Jan Humplik, Guy Lever, Tuomas Haarnoja, Leonard Hasenclever, Arunkumar Byravan, Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess:
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. CoRR abs/2405.02425 (2024) - 2023
- [i15]Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti:
Generative Adversarial Equilibrium Solvers. CoRR abs/2302.06607 (2023) - [i14]Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess:
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. CoRR abs/2304.13653 (2023) - [i13]Dhruva Tirumala, Thomas Lampe, José Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier:
Replay across Experiments: A Natural Extension of Off-Policy RL. CoRR abs/2311.15951 (2023) - 2022
- [j4]Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls:
Developing, evaluating and scaling learning agents in multi-agent environments. AI Commun. 35(4): 271-284 (2022) - [j3]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
From motor control to team play in simulated humanoid football. Sci. Robotics 7(69) (2022) - [d1]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". Zenodo, 2022
- [i12]Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls:
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments. CoRR abs/2209.10958 (2022) - 2021
- [i11]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
From Motor Control to Team Play in Simulated Humanoid Football. CoRR abs/2105.12196 (2021) - 2020
- [c17]Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos:
A Generalized Training Approach for Multiagent Learning. ICLR 2020
2010 – 2019
- 2019
- [c16]Dylan Banarse, Yoram Bachrach, Siqi Liu, Guy Lever, Nicolas Heess, Chrisantha Fernando, Pushmeet Kohli, Thore Graepel:
The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution. AAMAS 2019: 1134-1142 - [c15]Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel:
Emergent Coordination Through Competition. ICLR (Poster) 2019 - [c14]Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel:
Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. ALIFE 2019: 103-110 - [c13]Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel:
Biases for Emergent Communication in Multi-agent Reinforcement Learning. NeurIPS 2019: 13111-13121 - [i10]Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel:
Emergent Coordination Through Competition. CoRR abs/1902.07151 (2019) - [i9]Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos:
A Generalized Training Approach for Multiagent Learning. CoRR abs/1909.12823 (2019) - [i8]Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel:
Biases for Emergent Communication in Multi-agent Reinforcement Learning. CoRR abs/1912.05676 (2019) - 2018
- [c12]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. AAMAS 2018: 2085-2087 - [i7]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 abs/1807.01281 (2018) - 2017
- [c11]Aleksandar Botev, Guy Lever, David Barber:
Nesterov's accelerated gradient and momentum as approximations to regularised update descent. IJCNN 2017: 1899-1903 - [i6]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning. CoRR abs/1706.05296 (2017) - 2016
- [j2]Thomas Furmston, Guy Lever, David Barber:
Approximate Newton Methods for Policy Search in Markov Decision Processes. J. Mach. Learn. Res. 17: 227:1-227:51 (2016) - [c10]Guy Lever, John Shawe-Taylor, Ronnie Stafford, Csaba Szepesvári:
Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning. AAAI 2016: 1779-1787 - [i5]Aleksandar Botev, Guy Lever, David Barber:
Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent. CoRR abs/1607.01981 (2016) - 2015
- [c9]Guy Lever, Ronnie Stafford:
Modelling Policies in MDPs in Reproducing Kernel Hilbert Space. AISTATS 2015 - [i4]Thomas Furmston, Guy Lever:
A Gauss-Newton Method for Markov Decision Processes. CoRR abs/1507.08271 (2015) - 2014
- [c8]David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller:
Deterministic Policy Gradient Algorithms. ICML 2014: 387-395 - 2013
- [j1]Guy Lever, François Laviolette, John Shawe-Taylor:
Tighter PAC-Bayes bounds through distribution-dependent priors. Theor. Comput. Sci. 473: 4-28 (2013) - 2012
- [c7]Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton:
Modelling transition dynamics in MDPs with RKHS embeddings. ICML 2012 - [c6]Steffen Grünewälder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil:
Conditional mean embeddings as regressors. ICML 2012 - [c5]Guy Lever, Tom Diethe, John Shawe-Taylor:
Data dependent kernels in nearly-linear time. AISTATS 2012: 685-693 - [i3]Steffen Grünewälder, Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, Massimiliano Pontil:
Conditional mean embeddings as regressors - supplementary. CoRR abs/1205.4656 (2012) - [i2]Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton:
Modelling transition dynamics in MDPs with RKHS embeddings. CoRR abs/1206.4655 (2012) - 2011
- [b1]Guy Lever:
Exploiting structure defined by data in machine learning : some new analyses. University College London, UK, 2011 - [i1]Guy Lever, Tom Diethe, John Shawe-Taylor:
Data-dependent kernels in nearly-linear time. CoRR abs/1110.4416 (2011) - 2010
- [c4]Guy Lever, François Laviolette, John Shawe-Taylor:
Distribution-Dependent PAC-Bayes Priors. ALT 2010: 119-133 - [c3]Guy Lever:
Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction. AISTATS 2010: 437-444
2000 – 2009
- 2009
- [c2]Mark Herbster, Guy Lever:
Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation. COLT 2009 - 2008
- [c1]Mark Herbster, Guy Lever, Massimiliano Pontil:
Online Prediction on Large Diameter Graphs. NIPS 2008: 649-656
Coauthor Index
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last updated on 2024-10-21 21:28 CEST by the dblp team
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