Marc Lanctot
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
30
Venues
7
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
30 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Re-evaluating Open-ended Evaluation of Large Language Models. | Siqi Liu, Ian Gemp, Luke Marris, Georgios Piliouras, Nicolas Heess, Marc Lanctot |
| 2025 | ICML | Mastering Board Games by External and Internal Planning with Language Models. | John Schultz, Jakub Admek, 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 | IJCAI | Combining Deep Reinforcement Learning and Search with Generative Models for Game-Theoretic Opponent Modeling. | Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman |
| 2024 | AAAI | Learning Not to Regret. | David Sychrovsky, Michal Sustr, Elnaz Davoodi, Michael Bowling, Marc Lanctot, Martin Schmid |
| 2023 | ICLR | ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret. | Stephen Marcus McAleer, Gabriele Farina, Marc Lanctot, Tuomas Sandholm |
| 2023 | ICLR | A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games. | Samuel Sokota, Ryan D'Orazio, J. Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer |
| 2022 | ICML | Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games. | Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess |
| 2022 | IJCAI | Approximate Exploitability: Learning a Best Response. | Finbarr Timbers, Nolan Bard, Edward Lockhart, Marc Lanctot, Martin Schmid, Neil Burch, Julian Schrittwieser, Thomas Hubert, Michael Bowling |
| 2021 | AAAI | Hindsight and Sequential Rationality of Correlated Play. | Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy R. Greenwald, Michael Bowling |
| 2021 | AAAI | Solving Common-Payoff Games with Approximate Policy Iteration. | Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot |
| 2021 | ICML | Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers. | Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel |
| 2021 | ICML | Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. | Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy R. Greenwald |
| 2021 | ICML | From Poincar Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. | Julien Prolat, Rmi 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 | ICLR | A Generalized Training Approach for Multiagent Learning. | Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Prolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rmi Munos |
| 2020 | ICML | Fast computation of Nash Equilibria in Imperfect Information Games. | Rmi Munos, Julien Prolat, 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 |
| 2019 | AAAI | Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines. | Martin Schmid, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, Michael Bowling |
| 2019 | IJCAI | Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. | Edward Lockhart, Marc Lanctot, Julien Prolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls |
| 2018 | AAAI | Deep Q-learning From Demonstrations. | Todd Hester, Matej Vecerk, 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 | ICLR | Emergent Communication through Negotiation. | Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark |
| 2016 | GECCO | Convolution by Evolution: Differentiable Pattern Producing Networks. | Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra |
| 2016 | ICML | Dueling Network Architectures for Deep Reinforcement Learning. | Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas |
| 2015 | ICML | Fictitious Self-Play in Extensive-Form Games. | Johannes Heinrich, Marc Lanctot, David Silver |
| 2014 | ECAI | Minimizing Simple and Cumulative Regret in Monte-Carlo Tree Search. | Tom Pepels, Tristan Cazenave, Mark H. M. Winands, Marc Lanctot |
| 2014 | ECAI | Quality-based Rewards for Monte-Carlo Tree Search Simulations. | Tom Pepels, Mandy J. W. Tak, Marc Lanctot, Mark H. M. Winands |
| 2013 | IJCAI | Monte Carlo Tree Search in Simultaneous Move Games with Applications to Goofspiel. | Marc Lanctot, Viliam Lis, Mark H. M. Winands |
| 2013 | IJCAI | Monte Carlo *-Minimax Search. | Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands |
| 2012 | AAAI | Generalized Sampling and Variance in Counterfactual Regret Minimization. | Richard G. Gibson, Marc Lanctot, Neil Burch, Duane Szafron, Michael Bowling |
| 2012 | AAMAS | Efficient Nash equilibrium approximation through Monte Carlo counterfactual regret minimization. | Michael Johanson, Nolan Bard, Marc Lanctot, Richard G. Gibson, Michael Bowling |
| 2012 | ICML | No-Regret Learning in Extensive-Form Games with Imperfect Recall. | Marc Lanctot, Richard G. Gibson, Neil Burch, Michael Bowling |
| 2010 | AAAI | MCRNR: Fast Computing of Restricted Nash Responses by Means of Sampling. | Marc J. V. Ponsen, Marc Lanctot, Steven de Jong |