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The Value Equivalence Principle for Model-Based Reinforcement Learning

Nov 06, 2020
Christopher Grimm, André Barreto, Satinder Singh, David Silver

* NeurIPS-2020 

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Expected Eligibility Traces

Jul 03, 2020
Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa

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The Value-Improvement Path: Towards Better Representations for Reinforcement Learning

Jun 03, 2020
Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver

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Temporally-Extended ε-Greedy Exploration

Jun 02, 2020
Will Dabney, Georg Ostrovski, André Barreto

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Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement

Jan 30, 2019
André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel Mankowitz, Augustin Žídek, Rémi Munos

* Published at ICML 2018 

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Universal Successor Features Approximators

Dec 18, 2018
Diana Borsa, André Barreto, John Quan, Daniel Mankowitz, Rémi Munos, Hado van Hasselt, David Silver, Tom Schaul

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Fast deep reinforcement learning using online adjustments from the past

Oct 18, 2018
Steven Hansen, Pablo Sprechmann, Alexander Pritzel, André Barreto, Charles Blundell

* Accepted at NIPS 2018 

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Unicorn: Continual Learning with a Universal, Off-policy Agent

Jul 03, 2018
Daniel J. Mankowitz, Augustin Žídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul

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Successor Features for Transfer in Reinforcement Learning

Apr 12, 2018
André Barreto, Will Dabney, Rémi Munos, Jonathan J. Hunt, Tom Schaul, Hado van Hasselt, David Silver

* Published at NIPS 2017 

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