Marc Lanctot - RankMe

133 papers A* 26A 17Journal 75Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Active Evaluation of General Agents: Problem Definition and Comparison of Baseline Algorithms. CoRR Marc Lanctot, Kate Larson, Ian Gemp, Michael Kaisers
2026	J	`jnl`	Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models. CoRR Daniel Hennes, Zun Li, John Schultz, Marc Lanctot
2026	J	`jnl`	Discovering Multiagent Learning Algorithms with Large Language Models. CoRR Zun Li, John Schultz, Daniel Hennes, Marc Lanctot
2025	J	`jnl`	Code World Models for General Game Playing. CoRR Wolfgang Lehrach, Daniel Hennes, Miguel Lázaro-Gredilla, Xinghua Lou, Carter Wendelken, Zun Li, Antoine Dedieu, Jordi Grau-Moya, Marc Lanctot, Atil Iscen, John Schultz, Marcus Chiam, Ian Gemp, Piotr Zielinski, Satinder Singh, Kevin P. Murphy
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	J	`jnl`	Deviation Ratings: A General, Clone-Invariant Rating Method. CoRR Luke Marris, Siqi Liu, Ian Gemp, Georgios Piliouras, Marc Lanctot
2025	A	`conf`	Game of Thoughts: Iterative Reasoning in Game-Theoretic Domains with Large Language Models. AAMAS Benjamin Kempinski, Ian Gemp, Kate Larson, Marc Lanctot, Yoram Bachrach, Tal Kachman
2025	J	`jnl`	Jackpot! Alignment as a Maximal Lottery. CoRR Roberto-Rafael Maura-Rivero, Marc Lanctot, Francesco Visin, Kate Larson
2025	A	`conf`	Learning in Games with Progressive Hiding. AAMAS Benjamin Heymann, Marc Lanctot
2025	A*	`conf`	Mastering Board Games by External and Internal Planning with Language Models. ICML John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev
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
2025	A	`conf`	Soft Condorcet Optimization for Ranking of General Agents. AAMAS Marc Lanctot, Kate Larson, Michael Kaisers, Quentin Berthet, Ian Gemp, Manfred Diaz, Roberto-Rafael Maura-Rivero, Yoram Bachrach, Anna Koop, Doina Precup
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`	Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization. CoRR Luca D'Amico-Wong, Hugh Zhang, Marc Lanctot, David C. Parkes
2024	A*	`conf`	Learning Not to Regret. AAAI David Sychrovsky, Michal Sustr, Elnaz Davoodi, Michael Bowling, Marc Lanctot, Martin Schmid
2024	J	`jnl`	Learning in Games with progressive hiding. CoRR Benjamin Heymann, Marc Lanctot
2024	J	`jnl`	Mastering Board Games by External and Internal Planning with Language Models. CoRR John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev
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	J	`jnl`	Soft Condorcet Optimization for Ranking of General Agents. CoRR Marc Lanctot, Kate Larson, Michael Kaisers, Quentin Berthet, Ian Gemp, Manfred Diaz, Roberto-Rafael Maura-Rivero, Yoram Bachrach, Anna Koop, Doina Precup
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
2023	A*	`conf`	A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games. ICLR Samuel Sokota, Ryan D'Orazio, J. Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer
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	A*	`conf`	ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret. ICLR Stephen Marcus McAleer, Gabriele Farina, Marc Lanctot, Tuomas Sandholm
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`	Learning not to Regret. CoRR David Sychrovsky, Michal Sustr, Elnaz Davoodi, Marc Lanctot, Martin Schmid
2023	J	`jnl`	Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning. CoRR Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas W. Anthony, Julien Pérolat
2023	J	`jnl`	Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning. Trans. Mach. Learn. Res. Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas Anthony, Julien Pérolat
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`	A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games. CoRR Samuel Sokota, Ryan D'Orazio, J. Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer
2022	J	`jnl`	Anytime PSRO for Two-Player Zero-Sum Games. CoRR Stephen McAleer, Kevin Wang, John B. Lanier, Marc Lanctot, Pierre Baldi, Tuomas Sandholm, Roy Fox
2022	A*	`conf`	Approximate Exploitability: Learning a Best Response. IJCAI Finbarr Timbers, Nolan Bard, Edward Lockhart, Marc Lanctot, Martin Schmid, Neil Burch, Julian Schrittwieser, Thomas Hubert, Michael Bowling
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`	ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret. CoRR Stephen McAleer, Gabriele Farina, Marc Lanctot, Tuomas Sandholm
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	J	`jnl`	Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR 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
2022	A	`conf`	Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. AAMAS Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
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
2021	A*	`conf`	Dynamic population-based meta-learning for multi-agent communication with natural language. NeurIPS Abhinav Gupta, Marc Lanctot, Angeliki Lazaridou
2021	J	`jnl`	Dynamic population-based meta-learning for multi-agent communication with natural language. CoRR Abhinav Gupta, Marc Lanctot, Angeliki Lazaridou
2021	A*	`conf`	Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. ICML Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy R. Greenwald
2021	J	`jnl`	Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. CoRR Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy Greenwald
2021	A*	`conf`	From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. ICML Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
2021	A*	`conf`	Hindsight and Sequential Rationality of Correlated Play. AAAI Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy R. Greenwald, Michael Bowling
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
2021	J	`jnl`	Player of Games. CoRR Martin Schmid, Matej Moravcik, Neil Burch, Rudolf Kadlec, Joshua Davidson, Kevin Waugh, Nolan Bard, Finbarr Timbers, Marc Lanctot, G. Zacharias Holland, Elnaz Davoodi, Alden Christianson, Michael Bowling
2021	J	`jnl`	Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. CoRR Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
2021	A*	`conf`	Solving Common-Payoff Games with Approximate Policy Iteration. AAAI Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot
2021	J	`jnl`	Solving Common-Payoff Games with Approximate Policy Iteration. CoRR Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot
2021	A	`conf`	Sound Algorithms in Imperfect Information Games. AAMAS Michal Sustr, Martin Schmid, Matej Moravcík, Neil Burch, Marc Lanctot, Michael Bowling
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
2020	J	`jnl`	Approximate exploitability: Learning a best response in large games. CoRR Finbarr Timbers, Edward Lockhart, Martin Schmid, Marc Lanctot, Michael Bowling
2020	J	`jnl`	Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel
2020	A*	`conf`	Fast computation of Nash Equilibria in Imperfect Information Games. ICML 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
2020	J	`jnl`	From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. CoRR Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
2020	J	`jnl`	Hindsight and Sequential Rationality of Correlated Play. CoRR Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, Michael Bowling
2020	A*	`conf`	Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
2020	J	`jnl`	Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
2020	J	`jnl`	Negotiating Team Formation Using Deep Reinforcement Learning. CoRR Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
2020	J	`jnl`	Negotiating team formation using deep reinforcement learning. Artif. Intell. Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
2020	A	`conf`	Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. AAMAS 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
2020	J	`jnl`	Sound Search in Imperfect Information Games. CoRR Michal Sustr, Martin Schmid, Matej Moravcík, Neil Burch, Marc Lanctot, Michael Bowling
2020	J	`jnl`	The Advantage Regret-Matching Actor-Critic. CoRR 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
2020	J	`jnl`	The Hanabi challenge: A new frontier for AI research. Artif. Intell. Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
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	J	`jnl`	Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research. CoRR Joel Z. Leibo, Edward Hughes, Marc Lanctot, Thore Graepel
2019	A*	`conf`	Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. IJCAI Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
2019	J	`jnl`	Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. CoRR Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
2019	J	`jnl`	Neural Replicator Dynamics. CoRR Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls
2019	J	`jnl`	OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas W. Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis
2019	J	`jnl`	Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence. AI Mag. Guy Barash, Mauricio Castillo-Effen, Niyati Chhaya, Peter Clark, Huáscar Espinoza, Eitan Farchi, Christopher W. Geib, Odd Erik Gundersen, Seán Ó hÉigeartaigh, José Hernández-Orallo, Chiori Hori, Xiaowei Huang, Kokil Jaidka, Pavan Kapanipathi, Sarah Keren, Seokhwan Kim, Marc Lanctot, Danny Lange, Julian J. McAuley, David R. Martinez, Marwan Mattar, Mausam, Martin Michalowski, Reuth Mirsky, Roozbeh Mottaghi, Joseph C. Osborn, Julien Pérolat, Martin Schmid, Arash Shaban-Nejad, Onn Shehory, Biplav Srivastava, William W. Streilein, Kartik Talamadupula, Julian Togelius, Koichiro Yoshino, Quanshi Zhang, Imed Zitouni
2019	J	`jnl`	The Hanabi Challenge: A New Frontier for AI Research. CoRR Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
2019	A*	`conf`	Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines. AAAI Martin Schmid, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, Michael Bowling
2019	J	`jnl`	α-Rank: Multi-Agent Evaluation by Evolution. CoRR Shayegan Omidshafiei, Christos H. Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Pérolat, Rémi Munos
2018	A	`conf`	A Generalised Method for Empirical Game Theoretic Analysis. AAMAS Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
2018	J	`jnl`	A Generalised Method for Empirical Game Theoretic Analysis. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
2018	A*	`conf`	Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. NeurIPS Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling
2018	J	`jnl`	Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. CoRR Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling
2018	A*	`conf`	Deep Q-learning From Demonstrations. AAAI 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
2018	—	`conf`	Emergent Communication through Negotiation. ICLR (Poster) Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark
2018	J	`jnl`	Emergent Communication through Negotiation. CoRR Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark
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
2018	J	`jnl`	Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines. CoRR Martin Schmid, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, Michael Bowling
2017	—	`conf`	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
2017	J	`jnl`	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
2017	J	`jnl`	Learning from Demonstrations for Real World Reinforcement Learning. CoRR 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
2017	J	`jnl`	Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. CoRR David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, Demis Hassabis
2017	A	`conf`	Multi-agent Reinforcement Learning in Sequential Social Dilemmas. AAMAS Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel
2017	J	`jnl`	Multi-agent Reinforcement Learning in Sequential Social Dilemmas. CoRR Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel
2017	J	`jnl`	Symmetric Decomposition of Asymmetric Games. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
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`	Algorithms for computing strategies in two-player simultaneous move games. Artif. Intell. Branislav Bosanský, Viliam Lisý, Marc Lanctot, Jirí Cermák, Mark H. M. Winands
2016	A	`conf`	Convolution by Evolution: Differentiable Pattern Producing Networks. GECCO Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra
2016	J	`jnl`	Convolution by Evolution: Differentiable Pattern Producing Networks. CoRR Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra
2016	A*	`conf`	Dueling Network Architectures for Deep Reinforcement Learning. ICML Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas
2016	J	`jnl`	Mastering the game of Go with deep neural networks and tree search. Nat. David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy P. Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis
2016	—	`conf`	Memory-Efficient Backpropagation Through Time. NIPS Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves
2016	J	`jnl`	Memory-Efficient Backpropagation Through Time. CoRR Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves
2015	J	`jnl`	Dueling Network Architectures for Deep Reinforcement Learning. CoRR Ziyu Wang, Nando de Freitas, Marc Lanctot
2015	A*	`conf`	Fictitious Self-Play in Extensive-Form Games. ICML Johannes Heinrich, Marc Lanctot, David Silver
2015	A	`conf`	Online Monte Carlo Counterfactual Regret Minimization for Search in Imperfect Information Games. AAMAS Viliam Lisý, Marc Lanctot, Michael H. Bowling
2014	J	`jnl`	Computing Approximate Nash Equilibria and Robust Best-Responses Using Sampling. CoRR Marc J. V. Ponsen, Steven de Jong, Marc Lanctot
2014	A	`conf`	Further developments of extensive-form replicator dynamics using the sequence-form representation. AAMAS Marc Lanctot
2014	—	`conf`	Minimizing Simple and Cumulative Regret in Monte-Carlo Tree Search. CGW@ECAI Tom Pepels, Tristan Cazenave, Mark H. M. Winands, Marc Lanctot
2014	—	`conf`	Monte Carlo Tree Search variants for simultaneous move games. CIG Mandy J. W. Tak, Marc Lanctot, Mark H. M. Winands
2014	J	`jnl`	Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups. CoRR Marc Lanctot, Mark H. M. Winands, Tom Pepels, Nathan R. Sturtevant
2014	—	`conf`	Monte Carlo Tree Search with heuristic evaluations using implicit minimax backups. CIG Marc Lanctot, Mark H. M. Winands, Tom Pepels, Nathan R. Sturtevant
2014	A	`conf`	Quality-based Rewards for Monte-Carlo Tree Search Simulations. ECAI Tom Pepels, Mandy J. W. Tak, Marc Lanctot, Mark H. M. Winands
2014	J	`jnl`	Real-Time Monte Carlo Tree Search in Ms Pac-Man. IEEE Trans. Comput. Intell. AI Games Tom Pepels, Mark H. M. Winands, Marc Lanctot
2013	—	`conf`	Convergence of Monte Carlo Tree Search in Simultaneous Move Games. NIPS Viliam Lisý, Vojtech Kovarík, Marc Lanctot, Branislav Bosanský
2013	J	`jnl`	Convergence of Monte Carlo Tree Search in Simultaneous Move Games. CoRR Viliam Lisý, Vojtech Kovarík, Marc Lanctot, Branislav Bosanský
2013	—	`conf`	Improving Best-Reply Search. Computers and Games Markus Esser, Michael Gras, Mark H. M. Winands, Maarten P. D. Schadd, Marc Lanctot
2013	J	`jnl`	LOA Wins Lines of Action Tournament. ICGA J. Marc Lanctot, Mark H. M. Winands
2013	—	`conf`	Model AI Assignments 2013. EAAI Todd W. Neller, Marc Lanctot, Devika Subramanian, Stephanie E. August
2013	J	`jnl`	Monte Carlo *-Minimax Search CoRR Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands
2013	A*	`conf`	Monte Carlo *-Minimax Search. IJCAI Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands
2013	—	`conf`	Monte Carlo Tree Search in Simultaneous Move Games with Applications to Goofspiel. CGW@IJCAI Marc Lanctot, Viliam Lisý, Mark H. M. Winands
2013	J	`jnl`	SIA Wins Surakarta Tournament. ICGA J. Marc Lanctot, Mark H. M. Winands
2012	—	`conf`	Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions. NIPS Richard G. Gibson, Neil Burch, Marc Lanctot, Duane Szafron
2012	A	`conf`	Efficient Nash equilibrium approximation through Monte Carlo counterfactual regret minimization. AAMAS Michael Johanson, Nolan Bard, Marc Lanctot, Richard G. Gibson, Michael Bowling
2012	A*	`conf`	Generalized Sampling and Variance in Counterfactual Regret Minimization. AAAI Richard G. Gibson, Marc Lanctot, Neil Burch, Duane Szafron, Michael Bowling
2012	J	`jnl`	No-Regret Learning in Extensive-Form Games with Imperfect Recall CoRR Marc Lanctot, Richard G. Gibson, Neil Burch, Martin Zinkevich, Michael H. Bowling
2012	A*	`conf`	No-Regret Learning in Extensive-Form Games with Imperfect Recall. ICML Marc Lanctot, Richard G. Gibson, Neil Burch, Michael Bowling
2011	J	`jnl`	Computing Approximate Nash Equilibria and Robust Best-Responses Using Sampling. J. Artif. Intell. Res. Marc J. V. Ponsen, Steven de Jong, Marc Lanctot
2011	—	`conf`	Variance Reduction in Monte-Carlo Tree Search. NIPS Joel Veness, Marc Lanctot, Michael H. Bowling
2010	—	`conf`	MCRNR: Fast Computing of Restricted Nash Responses by Means of Sampling. Interactive Decision Theory and Game Theory Marc J. V. Ponsen, Marc Lanctot, Steven de Jong
2009	—	`conf`	Monte Carlo Sampling for Regret Minimization in Extensive Games. NIPS Marc Lanctot, Kevin Waugh, Martin Zinkevich, Michael H. Bowling
2007	—	`conf`	Adversarial Planning Through Strategy Simulation. CIG Franisek Sailer, Michael Buro, Marc Lanctot