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Temporal Abstraction in Reinforcement Learning with the Successor Representation


Oct 12, 2021
Marlos C. Machado, Andre Barreto, Doina Precup

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* 56 pages, 28 figures 

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Discovering Diverse Nearly Optimal Policies withSuccessor Features


Jun 01, 2021
Tom Zahavy, Brendan O'Donoghue, Andre Barreto, Volodymyr Mnih, Sebastian Flennerhag, Satinder Singh

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Coverage as a Principle for Discovering Transferable Behavior in Reinforcement Learning


Feb 24, 2021
Víctor Campos, Pablo Sprechmann, Steven Hansen, Andre Barreto, Steven Kapturowski, Alex Vitvitskyi, Adrià Puigdomènech Badia, Charles Blundell

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Discovering a set of policies for the worst case reward


Feb 08, 2021
Tom Zahavy, Andre Barreto, Daniel J Mankowitz, Shaobo Hou, Brendan O'Donoghue, Iurii Kemaev, Satinder Baveja Singh

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Temporal Difference Uncertainties as a Signal for Exploration


Oct 05, 2020
Sebastian Flennerhag, Jane X. Wang, Pablo Sprechmann, Francesco Visin, Alexandre Galashov, Steven Kapturowski, Diana L. Borsa, Nicolas Heess, Andre Barreto, Razvan Pascanu

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* 8 pages, 11 figures, 5 tables 

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Disentangled Cumulants Help Successor Representations Transfer to New Tasks


Nov 25, 2019
Christopher Grimm, Irina Higgins, Andre Barreto, Denis Teplyashin, Markus Wulfmeier, Tim Hertweck, Raia Hadsell, Satinder Singh

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General non-linear Bellman equations


Jul 08, 2019
Hado van Hasselt, John Quan, Matteo Hessel, Zhongwen Xu, Diana Borsa, Andre Barreto

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Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates


Jun 19, 2019
Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy Mann, Andre Barreto, Sylvain Gelly, Gergely Neu

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Fast Task Inference with Variational Intrinsic Successor Features


Jun 12, 2019
Steven Hansen, Will Dabney, Andre Barreto, Tom Van de Wiele, David Warde-Farley, Volodymyr Mnih

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Entropic Policy Composition with Generalized Policy Improvement and Divergence Correction


Dec 05, 2018
Jonathan J Hunt, Andre Barreto, Timothy P Lillicrap, Nicolas Heess

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