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Replay-Guided Adversarial Environment Design


Oct 06, 2021
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, Tim RocktÀschel

* NeurIPS 2021 

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Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers


Jul 26, 2021
Danielle Rothermel, Margaret Li, Tim RocktÀschel, Jakob Foerster

* Accepted to ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception 

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Implicit Communication as Minimum Entropy Coupling


Jul 17, 2021
Samuel Sokota, Christian Schroeder de Witt, Maximilian Igl, Luisa Zintgraf, Philip Torr, Shimon Whiteson, Jakob Foerster


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Centralized Model and Exploration Policy for Multi-Agent RL


Jul 14, 2021
Qizhen Zhang, Chris Lu, Animesh Garg, Jakob Foerster


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A New Formalism, Method and Open Issues for Zero-Shot Coordination


Jul 06, 2021
Johannes Treutlein, Michael Dennis, Caspar Oesterheld, Jakob Foerster


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Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings


Jun 16, 2021
Hengyuan Hu, Adam Lerer, Noam Brown, Jakob Foerster


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Quasi-Equivalence Discovery for Zero-Shot Emergent Communication


Mar 14, 2021
Kalesha Bullard, Douwe Kiela, Joelle Pineau, Jakob Foerster

* 14 pages 

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Off-Belief Learning


Mar 06, 2021
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, David Wu, Noam Brown, Jakob Foerster


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Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian


Nov 12, 2020
Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alex Peysakhovich, Aldo Pacchiano, Jakob Foerster

* Camera-ready version, NeurIPS 2020 

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Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations


Oct 29, 2020
Kalesha Bullard, Franziska Meier, Douwe Kiela, Joelle Pineau, Jakob Foerster


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The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets


Sep 23, 2020
Oana-Maria Camburu, Eleonora Giunchiglia, Jakob Foerster, Thomas Lukasiewicz, Phil Blunsom


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Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning


Mar 19, 2020
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder de Witt, Gregory Farquhar, Jakob Foerster, Shimon Whiteson

* Extended version of our ICML 2018 paper (arXiv:1803.11485) 

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"Other-Play" for Zero-Shot Coordination


Mar 09, 2020
Hengyuan Hu, Adam Lerer, Alex Peysakhovich, Jakob Foerster


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On the interaction between supervision and self-play in emergent communication


Feb 04, 2020
Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau

* The first two authors contributed equally. Accepted at ICLR 2020 

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Improving Policies via Search in Cooperative Partially Observable Games


Dec 05, 2019
Adam Lerer, Hengyuan Hu, Jakob Foerster, Noam Brown

* AAAI 2020 

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Capacity, Bandwidth, and Compositionality in Emergent Language Learning


Oct 24, 2019
Cinjon Resnick, Abhinav Gupta, Jakob Foerster, Andrew M. Dai, Kyunghyun Cho

* The first two authors contributed equally 

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Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods


Oct 09, 2019
Oana-Maria Camburu, Eleonora Giunchiglia, Jakob Foerster, Thomas Lukasiewicz, Phil Blunsom

* NeurIPS 2019 Workshop Safety and Robustness in Decision Making 

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Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning


Sep 23, 2019
Gregory Farquhar, Shimon Whiteson, Jakob Foerster


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A Survey of Reinforcement Learning Informed by Natural Language


Jun 10, 2019
Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim RocktÀschel

* Published at IJCAI'19 

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Differentiable Game Mechanics


May 13, 2019
Alistair Letcher, David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel

* Journal of Machine Learning Research (JMLR), v20 (84) 1-40, 2019 
* JMLR 2019, journal version of arXiv:1802.05642 

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On the Pitfalls of Measuring Emergent Communication


Mar 12, 2019
Ryan Lowe, Jakob Foerster, Y-Lan Boureau, Joelle Pineau, Yann Dauphin

* AAMAS 2019. 13 pages 

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The StarCraft Multi-Agent Challenge


Feb 26, 2019
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob Foerster, Shimon Whiteson


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Stable Opponent Shaping in Differentiable Games


Nov 20, 2018
Alistair Letcher, Jakob Foerster, David Balduzzi, Tim RocktÀschel, Shimon Whiteson

* 20 pages, 7 figures 

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DiCE: The Infinitely Differentiable Monte-Carlo Estimator


Sep 19, 2018
Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim RocktÀschel, Eric P. Xing, Shimon Whiteson


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QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning


Jun 06, 2018
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder de Witt, Gregory Farquhar, Jakob Foerster, Shimon Whiteson

* Camera-ready version, International Conference of Machine Learning 2018 

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The Mechanics of n-Player Differentiable Games


Jun 06, 2018
David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel

* PMLR volume 80, 2018 
* ICML 2018, final version 

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Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning


May 21, 2018
Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson

* Camera-ready version, International Conference of Machine Learning 2017; updated to fix print-breaking image 

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Counterfactual Multi-Agent Policy Gradients


Dec 14, 2017
Jakob Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson


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