Luke Marris

40 papers A* 12A 3Journal 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deep Incentive Design with Differentiable Equilibrium Blocks.
CoRR
Vinzenz Thoma, Georgios Piliouras, Luke Marris
2025 A* conf
Combining Deep Reinforcement Learning and Search with Generative Models for Game-Theoretic Opponent Modeling.
IJCAI
Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman
2025 A* conf
Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning.
ICML
Ian Gemp, Andreas Alexander Haupt, Luke Marris, Siqi Liu, Georgios Piliouras
2025 J jnl
Deviation Ratings: A General, Clone-Invariant Rating Method.
CoRR
Luke Marris, Siqi Liu, Ian Gemp, Georgios Piliouras, Marc Lanctot
2025 A* conf
Re-evaluating Open-ended Evaluation of Large Language Models.
ICLR
Siqi Liu, Ian Gemp, Luke Marris, Georgios Piliouras, Nicolas Heess, Marc Lanctot
2025 J jnl
Re-evaluating Open-ended Evaluation of Large Language Models.
CoRR
Siqi Liu, Ian Gemp, Luke Marris, Georgios Piliouras, Nicolas Heess, Marc Lanctot
2024 A* conf
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization.
ICLR
Ian Gemp, Luke Marris, Georgios Piliouras
2024 A conf
Approximating the Core via Iterative Coalition Sampling.
AAMAS
Ian Gemp, Marc Lanctot, Luke Marris, Yiran Mao, Edgar A. Duéñez-Guzmán, Sarah Perrin, András György, Romuald Elie, Georgios Piliouras, Michael Kaisers, Daniel Hennes, Kalesha Bullard, Kate Larson, Yoram Bachrach
2024 J jnl
Approximating the Core via Iterative Coalition Sampling.
CoRR
Ian Gemp, Marc Lanctot, Luke Marris, Yiran Mao, Edgar A. Duéñez-Guzmán, Sarah Perrin, András György, Romuald Elie, Georgios Piliouras, Michael Kaisers, Daniel Hennes, Kalesha Bullard, Kate Larson, Yoram Bachrach
2024 J jnl
Convex Markov Games: A Framework for Fairness, Imitation, and Creativity in Multi-Agent Learning.
CoRR
Ian Gemp, Andreas A. Haupt, Luke Marris, Siqi Liu, Georgios Piliouras
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 A conf
Neural Population Learning beyond Symmetric Zero-Sum Games.
AAMAS
Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess
2024 J jnl
Neural Population Learning beyond Symmetric Zero-sum Games.
CoRR
Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess
2024 A* conf
NfgTransformer: Equivariant Representation Learning for Normal-form Games.
ICLR
Siqi Liu, Luke Marris, Georgios Piliouras, Ian Gemp, Nicolas Heess
2024 J jnl
NfgTransformer: Equivariant Representation Learning for Normal-form Games.
CoRR
Siqi Liu, Luke Marris, Georgios Piliouras, Ian Gemp, Nicolas Heess
2024 J jnl
States as Strings as Strategies: Steering Language Models with Game-Theoretic Solvers.
CoRR
Ian Gemp, Yoram Bachrach, Marc Lanctot, Roma Patel, Vibhavari Dasagi, Luke Marris, Georgios Piliouras, Siqi Liu, Karl Tuyls
2024 J jnl
Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package.
CoRR
Luke Marris, Ian Gemp, Siqi Liu, Joel Z. Leibo, Georgios Piliouras
2023 J jnl
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization.
CoRR
Ian Gemp, Luke Marris, Georgios Piliouras
2023 J jnl
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning.
CoRR
Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman
2023 J jnl
Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of 2×2 Normal-Form Games.
CoRR
Luke Marris, Ian Gemp, Georgios Piliouras
2023 J jnl
Evaluating Agents using Social Choice Theory.
CoRR
Marc Lanctot, Kate Larson, Yoram Bachrach, Luke Marris, Zun Li, Avishkar Bhoopchand, Thomas W. Anthony, Brian Tanner, Anna Koop
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 A conf
Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games.
AAMAS
Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Kate Larson, Yoram Bachrach, Michael P. Wellman, Paul Muller
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
2022 J jnl
Game Theoretic Rating in N-player general-sum games with Equilibria.
CoRR
Luke Marris, Marc Lanctot, Ian Gemp, Shayegan Omidshafiei, Stephen McAleer, Jerome T. Connor, Karl Tuyls, Thore Graepel
2022 A* conf
NeuPL: Neural Population Learning.
ICLR
Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel
2022 J jnl
NeuPL: Neural Population Learning.
CoRR
Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel
2022 A* conf
Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games.
ICML
Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess
2022 J jnl
Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games.
CoRR
Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess
2022 A* conf
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers.
NeurIPS
Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls
2022 J jnl
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers.
CoRR
Luke Marris, Ian Gemp, Thomas W. Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls
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
2021 A* conf
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers.
ICML
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel
2021 J jnl
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers.
CoRR
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel
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
2018 A* conf
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.
NeurIPS
Sergey Bartunov, Adam Santoro, Blake A. Richards, Luke Marris, Geoffrey E. Hinton, Timothy P. Lillicrap
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