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VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning


Oct 18, 2019
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson


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Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments


Oct 16, 2019
RĂ©my Portelas, CĂ©dric Colas, Katja Hofmann, Pierre-Yves Oudeyer

* Accepted at CoRL 2019 

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Combining No-regret and Q-learning


Oct 07, 2019
Ian A. Kash, Michael Sullins, Katja Hofmann


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Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games


Jun 04, 2019
Aristide Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann


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The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors


Apr 22, 2019
William H. Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noboru Kuno, Stephanie Milani, Sharada Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang

* accepted at NeurIPS 2019, 28 pages 

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The Multi-Agent Reinforcement Learning in MalmĂ– (MARLĂ–) Competition


Jan 23, 2019
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, Andre Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita

* Challenges in Machine Learning (NIPS Workshop), 2018 
* 2 pages plus references 

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Successor Uncertainties: exploration and uncertainty in temporal difference learning


Oct 15, 2018
David Janz, Jiri Hron, José Miguel Hernández-Lobato, Katja Hofmann, Sebastian Tschiatschek


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CAML: Fast Context Adaptation via Meta-Learning


Oct 12, 2018
Luisa M Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson


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Meta Reinforcement Learning with Latent Variable Gaussian Processes


Jul 07, 2018
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth

* 11 pages, 7 figures 

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Depth and nonlinearity induce implicit exploration for RL


May 29, 2018
Justas Dauparas, Ryota Tomioka, Katja Hofmann


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