Guy Lever

42 papers A* 9A 5B 2C 1Misc 1Journal 21Unranked 2
YearRankTypeTitle / Venue / Authors
2024 A* conf
Generative Adversarial Equilibrium Solvers.
ICLR
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
2024 Misc conf
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning.
CoRL
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
2024 J jnl
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning.
CoRR
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
2024 J jnl
Learning agile soccer skills for a bipedal robot with deep reinforcement learning.
Sci. Robotics
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
2024 A* conf
Replay across Experiments: A Natural Extension of Off-Policy RL.
ICLR
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
2023 J jnl
Generative Adversarial Equilibrium Solvers.
CoRR
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
2023 J jnl
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning.
CoRR
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
2023 J jnl
Replay across Experiments: A Natural Extension of Off-Policy RL.
CoRR
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
2022 J jnl
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments.
CoRR
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
2022 J jnl
Developing, evaluating and scaling learning agents in multi-agent environments.
AI Commun.
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
2022 J jnl
From motor control to team play in simulated humanoid football.
Sci. Robotics
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
2021 J jnl
From Motor Control to Team Play in Simulated Humanoid Football.
CoRR
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
2020 A* conf
A Generalized Training Approach for Multiagent Learning.
ICLR
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
2019 J jnl
A Generalized Training Approach for Multiagent Learning.
CoRR
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
2019 A* conf
Biases for Emergent Communication in Multi-agent Reinforcement Learning.
NeurIPS
Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
2019 J jnl
Biases for Emergent Communication in Multi-agent Reinforcement Learning.
CoRR
Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
2019 — conf
Emergent Coordination Through Competition.
ICLR (Poster)
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel
2019 J jnl
Emergent Coordination Through Competition.
CoRR
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel
2019 C conf
Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems.
ALIFE
Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel
2019 A conf
The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution.
AAMAS
Dylan Banarse, Yoram Bachrach, Siqi Liu, Guy Lever, Nicolas Heess, Chrisantha Fernando, Pushmeet Kohli, Thore Graepel
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
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward.
AAMAS
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
2017 B conf
Nesterov's accelerated gradient and momentum as approximations to regularised update descent.
IJCNN
Aleksandar Botev, Guy Lever, David Barber
2017 J jnl
Value-Decomposition Networks For Cooperative Multi-Agent Learning.
CoRR
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
2016 J jnl
Approximate Newton Methods for Policy Search in Markov Decision Processes.
J. Mach. Learn. Res.
Thomas Furmston, Guy Lever, David Barber
2016 A* conf
Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning.
AAAI
Guy Lever, John Shawe-Taylor, Ronnie Stafford, Csaba Szepesvári
2016 J jnl
Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent.
CoRR
Aleksandar Botev, Guy Lever, David Barber
2015 J jnl
A Gauss-Newton Method for Markov Decision Processes.
CoRR
Thomas Furmston, Guy Lever
2015 A conf
Modelling Policies in MDPs in Reproducing Kernel Hilbert Space.
AISTATS
Guy Lever, Ronnie Stafford
2014 A* conf
Deterministic Policy Gradient Algorithms.
ICML
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller
2013 J jnl
Tighter PAC-Bayes bounds through distribution-dependent priors.
Theor. Comput. Sci.
Guy Lever, François Laviolette, John Shawe-Taylor
2012 J jnl
Conditional mean embeddings as regressors - supplementary
CoRR
Steffen Grünewälder, Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, Massimiliano Pontil
2012 A* conf
Conditional mean embeddings as regressors.
ICML
Steffen Grünewälder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil
2012 A conf
Data dependent kernels in nearly-linear time.
AISTATS
Guy Lever, Tom Diethe, John Shawe-Taylor
2012 J jnl
Modelling transition dynamics in MDPs with RKHS embeddings
CoRR
Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton
2012 A* conf
Modelling transition dynamics in MDPs with RKHS embeddings.
ICML
Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton
2011 J jnl
Data-dependent kernels in nearly-linear time
CoRR
Guy Lever, Tom Diethe, John Shawe-Taylor
2011 — —
Exploiting structure defined by data in machine learning : some new analyses.
Guy Lever
2010 B conf
Distribution-Dependent PAC-Bayes Priors.
ALT
Guy Lever, François Laviolette, John Shawe-Taylor
2010 A conf
Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction.
AISTATS
Guy Lever
2009 A* conf
Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation.
COLT
Mark Herbster, Guy Lever
2008 — conf
Online Prediction on Large Diameter Graphs.
NIPS
Mark Herbster, Guy Lever, Massimiliano Pontil