Guy Lever

According to our database, Guy Lever authored at least 30 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Replay across Experiments: A Natural Extension of Off-Policy RL.

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

CoRR, 2023

Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning.

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

CoRR, 2023

Generative Adversarial Equilibrium Solvers.

Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti

CoRR, 2023

2022

From motor control to team play in simulated humanoid football.

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

Sci. Robotics, 2022

Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments.

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

CoRR, 2022

Developing, evaluating and scaling learning agents in multi-agent environments.

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

AI Commun., 2022

2020

A Generalized Training Approach for Multiagent Learning.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Biases for Emergent Communication in Multi-agent Reinforcement Learning.

Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems.

Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel

Proceedings of the 2019 Conference on Artificial Life, 2019

Emergent Coordination Through Competition.

Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel

Proceedings of the 7th International Conference on Learning Representations, 2019

The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution.

Dylan Banarse, Yoram Bachrach, Siqi Liu, Guy Lever, Nicolas Heess, Chrisantha Fernando, Pushmeet Kohli, Thore Graepel

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.

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

CoRR, 2018

Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward.

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

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Value-Decomposition Networks For Cooperative Multi-Agent Learning.

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

CoRR, 2017

Nesterov's accelerated gradient and momentum as approximations to regularised update descent.

Aleksandar Botev, Guy Lever, David Barber

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

Approximate Newton Methods for Policy Search in Markov Decision Processes.

Thomas Furmston, Guy Lever, David Barber

J. Mach. Learn. Res., 2016

Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning.

Guy Lever, John Shawe-Taylor, Ronnie Stafford, Csaba Szepesvári

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

A Gauss-Newton Method for Markov Decision Processes.

Thomas Furmston, Guy Lever

CoRR, 2015

Modelling Policies in MDPs in Reproducing Kernel Hilbert Space.

Guy Lever, Ronnie Stafford

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Deterministic Policy Gradient Algorithms.

David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Tighter PAC-Bayes bounds through distribution-dependent priors.

Guy Lever, François Laviolette, John Shawe-Taylor

Theor. Comput. Sci., 2013

2012

Data dependent kernels in nearly-linear time.

Guy Lever, Tom Diethe, John Shawe-Taylor

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Conditional mean embeddings as regressors - supplementary

Steffen Grünewälder, Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, Massimiliano Pontil

CoRR, 2012

Conditional mean embeddings as regressors.

Steffen Grünewälder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil

Proceedings of the 29th International Conference on Machine Learning, 2012

Modelling transition dynamics in MDPs with RKHS embeddings.

Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Exploiting structure defined by data in machine learning : some new analyses.

Guy Lever

PhD thesis, 2011

2010

Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction.

Guy Lever

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Distribution-Dependent PAC-Bayes Priors.

Guy Lever, François Laviolette, John Shawe-Taylor

Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009

Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation.

Mark Herbster, Guy Lever

Proceedings of the COLT 2009, 2009

2008

Online Prediction on Large Diameter Graphs.

Mark Herbster, Guy Lever, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 21, 2008