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* [[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 ...==
* [[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]], [[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=
