Difference between revisions of "Marc Lanctot"

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* [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2018'''). ''[http://science.sciencemag.org/content/362/6419/1140 A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play]''. [https://en.wikipedia.org/wiki/Science_(journal) Science], Vol. 362, No. 6419 <ref>[https://deepmind.com/blog/alphazero-shedding-new-light-grand-games-chess-shogi-and-go/ AlphaZero: Shedding new light on the grand games of chess, shogi and Go] by [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]] and [[Demis Hassabis]], [[DeepMind]], December 03, 2018</ref>
 
* [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2018'''). ''[http://science.sciencemag.org/content/362/6419/1140 A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play]''. [https://en.wikipedia.org/wiki/Science_(journal) Science], Vol. 362, No. 6419 <ref>[https://deepmind.com/blog/alphazero-shedding-new-light-grand-games-chess-shogi-and-go/ AlphaZero: Shedding new light on the grand games of chess, shogi and Go] by [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]] and [[Demis Hassabis]], [[DeepMind]], December 03, 2018</ref>
 
* [[Edward Lockhart]], [[Marc Lanctot]], [[Julien Pérolat]], [[Jean-Baptiste Lespiau]], [[Dustin Morrill]], [[Finbarr Timbers]], [[Karl Tuyls]] ('''2019'''). ''Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent''. [https://arxiv.org/abs/1903.05614 arXiv:1903.05614]
 
* [[Edward Lockhart]], [[Marc Lanctot]], [[Julien Pérolat]], [[Jean-Baptiste Lespiau]], [[Dustin Morrill]], [[Finbarr Timbers]], [[Karl Tuyls]] ('''2019'''). ''Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent''. [https://arxiv.org/abs/1903.05614 arXiv:1903.05614]
* [[Marc Lanctot]], [[Edward Lockhart]], [[Jean-Baptiste Lespiau]], [[Vinicius 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 Anthony]], [[Edward Hughes]], [[Ivo Danihelka]], [[Jonah Ryan-Davis]] ('''2019'''). ''OpenSpiel: A Framework for Reinforcement Learning in Games''. [https://arxiv.org/abs/1908.09453 arXiv:1908.09453] <ref>[https://github.com/deepmind/open_spiel/blob/master/docs/contributing.md open_spiel/contributing.md at master · deepmind/open_spiel · GitHub]</ref>
+
* [[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 Anthony]], [[Edward Hughes]], [[Ivo Danihelka]], [[Jonah Ryan-Davis]] ('''2019'''). ''OpenSpiel: A Framework for Reinforcement Learning in Games''. [https://arxiv.org/abs/1908.09453 arXiv:1908.09453] <ref>[https://github.com/deepmind/open_spiel/blob/master/docs/contributing.md open_spiel/contributing.md at master · deepmind/open_spiel · GitHub]</ref>
 
==2020 ...==
 
==2020 ...==
* [[Finbarr Timbers]], [[Edward Lockhart]], [[Martin Schmid]], [[Marc Lanctot]], [[Michael Bowling]] ('''2020'''). ''Approximate exploitability: Learning a best response in large games''. [https://arxiv.org/abs/2004.09677 arXiv:2004.09677]
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* [[Finbarr Timbers]], [[Edward Lockhart]], [[Mathematician#MSchmid|Martin Schmid]], [[Marc Lanctot]], [[Michael Bowling]] ('''2020'''). ''Approximate exploitability: Learning a best response in large games''. [https://arxiv.org/abs/2004.09677 arXiv:2004.09677]
* [[Samuel Sokota]], [[Edward Lockhart]], [[Finbarr Timbers]], [[Elnaz Davoodi]], [[Ryan D'Orazio]], [[Neil Burch]], [[Martin Schmid]], [[Michael Bowling]], [[Marc Lanctot]] ('''2021'''). ''Solving Common-Payoff Games with Approximate Policy Iteration''. [https://arxiv.org/abs/2101.04237 arXiv:2101.04237]
+
* [[Samuel Sokota]], [[Edward Lockhart]], [[Finbarr Timbers]], [[Elnaz Davoodi]], [[Ryan D'Orazio]], [[Neil Burch]],[[Mathematician#MSchmid|Martin Schmid]], [[Michael Bowling]], [[Marc Lanctot]] ('''2021'''). ''Solving Common-Payoff Games with Approximate Policy Iteration''. [https://arxiv.org/abs/2101.04237 arXiv:2101.04237]
  
 
=External Links=  
 
=External Links=  

Latest revision as of 15:19, 30 May 2021

Home * People * Marc Lanctot

Marc Lanctot [1]

Marc Lanctot,
a Canadian computer scientist at Google DeepMind involved in the AlphaZero project, and before post-doctoral researcher for the Maastricht University Games and AI Group [2] of Mark Winands. He holds a M.Sc. from McGill University in 2005 [3] , and a Ph.D. from University of Alberta in 2013 [4] . Marc is generally interested in AI, machine learning, and games. His current research focus is on sampling algorithms for equilibrium computation and decision-making, as well as variants of Monte-Carlo Tree Search.

Selected Publications

[5]

2005 ...

2010 ...

2015 ...

2020 ...

External Links

References

  1. Marc Lanctot's Web Page
  2. Games and AI Group
  3. Marc Lanctot (2005). Adaptive Virtual Environments in Multi-player Computer Games. MSc. Thesis, McGill University
  4. Marc Lanctot (2013). Monte Carlo Sampling and Regret Minimization for Equilibrium Computation and Decision-Making in Large Extensive Form Games. Ph.D. thesis, University of Alberta, advisor Michael Bowling
  5. dblp: Marc Lanctot
  6. AlphaZero: Shedding new light on the grand games of chess, shogi and Go by David Silver, Thomas Hubert, Julian Schrittwieser and Demis Hassabis, DeepMind, December 03, 2018
  7. open_spiel/contributing.md at master · deepmind/open_spiel · GitHub

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