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Game Plan: What AI can do for Football, and What Football can do for AI

Nov 18, 2020
Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adria Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Perolat, Bart De Vylder, Ali Eslami, Mark Rowland, Andrew Jaegle, Remi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis


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Navigating the Landscape of Games

May 04, 2020
Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome Connor, Daniel Hennes, Paul Muller, Julien Perolat, Bart De Vylder, Audrunas Gruslys, Remi Munos


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Real World Games Look Like Spinning Tops

Apr 20, 2020
Wojciech Marian Czarnecki, Gauthier Gidel, Brendan Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg


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From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization

Feb 19, 2020
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls

* 43 pages 

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Multiagent Evaluation under Incomplete Information

Oct 30, 2019
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Perolat, Michal Valko, Georgios Piliouras, Remi Munos


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OpenSpiel: A Framework for Reinforcement Learning in Games

Oct 10, 2019
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


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A Generalized Training Approach for Multiagent Learning

Sep 27, 2019
Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Perolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Remi Munos


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Neural Replicator Dynamics

Jun 01, 2019
Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Remi Munos, Julien Perolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls


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Policy Distillation and Value Matching in Multiagent Reinforcement Learning

Mar 15, 2019
Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How

* Submitted as a conference paper to IROS 2019 

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Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

Mar 07, 2019
Dong Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How


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Learning to Teach in Cooperative Multiagent Reinforcement Learning

Aug 31, 2018
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How


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Crossmodal Attentive Skill Learner

May 22, 2018
Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How

* International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018, NIPS 2017 Deep Reinforcement Learning Symposium 

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Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions

Aug 18, 2017
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How

* Accepted to the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) 

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Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability

Jul 13, 2017
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian

* Proceedings of the 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia, PMLR 70:2681-2690, 2017 
* Accepted to ICML 2017 

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Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces

Mar 16, 2017
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian


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Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations

Mar 16, 2017
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T. Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian


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Hierarchical Bayesian Noise Inference for Robust Real-time Probabilistic Object Classification

Jul 14, 2016
Shayegan Omidshafiei, Brett T. Lopez, Jonathan P. How, John Vian


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Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions

Feb 20, 2015
Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Jonathan P. How


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