Guy Lever

ORCID

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 24

Top Venues

University College London, UK (PHD)

Education History

University College London, UK

PHD

Publications

Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
Generative Adversarial Equilibrium Solvers. CoRR (2023)
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 (2023)
Dhruva Tirumala, Thomas Lampe, Jose 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 (2023)
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)
Ian M. 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) (2022)
Ian M. Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar 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 (2022)
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 (2021)
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)
Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
Biases for Emergent Communication in Multi-agent Reinforcement Learning. NeurIPS (2019)
Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
Biases for Emergent Communication in Multi-agent Reinforcement Learning. CoRR (2019)
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)
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel
Emergent Coordination Through Competition. CoRR (2019)
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel
Emergent Coordination Through Competition. ICLR (Poster) (2019)
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)
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 (2019)
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)
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)
Aleksandar Botev, Guy Lever, David Barber
Nesterov's accelerated gradient and momentum as approximations to regularised update descent. IJCNN (2017)
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 (2017)
Thomas Furmston, Guy Lever, David Barber
Approximate Newton Methods for Policy Search in Markov Decision Processes. J. Mach. Learn. Res. 17 (2016)
Aleksandar Botev, Guy Lever, David Barber
Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent. CoRR (2016)
Guy Lever, John Shawe-Taylor, Ronnie Stafford, Csaba Szepesvári
Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning. AAAI (2016)
Thomas Furmston, Guy Lever
A Gauss-Newton Method for Markov Decision Processes. CoRR (2015)
Guy Lever, Ronnie Stafford
Modelling Policies in MDPs in Reproducing Kernel Hilbert Space. AISTATS (2015)
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller
Deterministic Policy Gradient Algorithms. ICML (2014)
Guy Lever, François Laviolette, John Shawe-Taylor
Tighter PAC-Bayes bounds through distribution-dependent priors. Theor. Comput. Sci. 473 (2013)
Guy Lever, Tom Diethe, John Shawe-Taylor
Data dependent kernels in nearly-linear time. AISTATS (2012)
Steffen Grünewälder, Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, Massimiliano Pontil
Conditional mean embeddings as regressors - supplementary CoRR (2012)
Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton
Modelling transition dynamics in MDPs with RKHS embeddings CoRR (2012)
Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton
Modelling transition dynamics in MDPs with RKHS embeddings. ICML (2012)
Steffen Grünewälder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil
Conditional mean embeddings as regressors. ICML (2012)
Guy Lever, Tom Diethe, John Shawe-Taylor
Data-dependent kernels in nearly-linear time CoRR (2011)
Guy Lever
Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction. AISTATS (2010)
Guy Lever, François Laviolette, John Shawe-Taylor
Distribution-Dependent PAC-Bayes Priors. ALT (2010)
Mark Herbster, Guy Lever
Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation. COLT (2009)
Mark Herbster, Guy Lever, Massimiliano Pontil
Online Prediction on Large Diameter Graphs. NIPS (2008)

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Publication Activity (10 Years)

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Guy Lever