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Local Search for Policy Iteration in Continuous Control

Oct 12, 2020
Jost Tobias Springenberg, Nicolas Heess, Daniel Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin Riedmiller


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RL Unplugged: Benchmarks for Offline Reinforcement Learning

Jul 02, 2020
Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gomez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas

* 21 pages including supplementary material, the github link for the datasets: https://github.com/deepmind/deepmind-research/rl_unplugged 

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A Bayesian Approach to Robust Reinforcement Learning

May 20, 2019
Esther Derman, Daniel Mankowitz, Timothy Mann, Shie Mannor

* Accepted to UAI 2019 

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Challenges of Real-World Reinforcement Learning

Apr 29, 2019
Gabriel Dulac-Arnold, Daniel Mankowitz, Todd Hester


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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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