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Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games


May 31, 2022
Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess


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Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel


May 25, 2022
Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio


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Data augmentation for efficient learning from parametric experts


May 23, 2022
Alexandre Galashov, Josh Merel, Nicolas Heess


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A Generalist Agent


May 19, 2022
Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas


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Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach


Apr 22, 2022
Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin Riedmiller


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Revisiting Gaussian mixture critic in off-policy reinforcement learning: a sample-based approach


Apr 21, 2022
Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin Riedmiller


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COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation


Apr 19, 2022
Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez

* 24 pages, 6 figures, Accepted at ICLR 2022 (spotlight) 

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Offline Distillation for Robot Lifelong Learning with Imbalanced Experience


Apr 12, 2022
Wenxuan Zhou, Steven Bohez, Jan Humplik, Abbas Abdolmaleki, Dushyant Rao, Markus Wulfmeier, Tuomas Haarnoja, Nicolas Heess


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