Audrunas Gruslys

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 18

Top Topics

Learning Agents

Reinforcement Learning

Replicator Dynamics

Multiagent Learning

Top Venues

Publications

Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rémi Munos
Quantile Credit Assignment. ICML (2023)
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)
Audrunas Gruslys, Marc Lanctot, Rémi Munos, Finbarr Timbers, Martin Schmid, Julien Pérolat, Dustin Morrill, Vinícius Flores Zambaldi, Jean-Baptiste Lespiau, John Schultz, Mohammad Gheshlaghi Azar, Michael Bowling, Karl Tuyls
The Advantage Regret-Matching Actor-Critic. CoRR (2020)
Daniel Hennes, Dustin Morrill, Shayegan Omidshafiei, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Paavo Parmas, Edgar A. Duéñez-Guzmán, Karl Tuyls
Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. AAMAS (2020)
Rémi Munos, Julien Pérolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls
Fast computation of Nash Equilibria in Imperfect Information Games. ICML (2020)
Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome T. Connor, Daniel Hennes, Paul Muller, Julien Pérolat, Bart De Vylder, Audrunas Gruslys, Rémi Munos
Navigating the Landscape of Games. CoRR (2020)
Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls
Neural Replicator Dynamics. 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)
Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
Deep Q-learning From Demonstrations. AAAI (2018)
Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran, David Amos, Charles Beattie, Keith Anderson, Antonio García Castañeda, Manuel Sanchez, Simon Green, Audrunas Gruslys, Shane Legg, Demis Hassabis, Matthew Botvinick
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. CoRR (2018)
Audrunas Gruslys, Will Dabney, Mohammad Gheshlaghi Azar, Bilal Piot, Marc G. Bellemare, Rémi Munos
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning. ICLR (Poster) (2018)
Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
Learning from Demonstrations for Real World Reinforcement Learning. CoRR (2017)
Audrunas Gruslys, Mohammad Gheshlaghi Azar, Marc G. Bellemare, Rémi Munos
The Reactor: A Sample-Efficient Actor-Critic Architecture. CoRR (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)
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)
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)
Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves
Memory-Efficient Backpropagation Through Time. CoRR (2016)
Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves
Memory-Efficient Backpropagation Through Time. NIPS (2016)
Audrunas Gruslys, Julio Acosta-Cabronero, Peter J. Nestor, Guy B. Williams, Richard E. Ansorge
A New Fast Accurate Nonlinear Medical Image Registration Program Including Surface Preserving Regularization. IEEE Trans. Medical Imaging 33 (11) (2014)