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In-context Reinforcement Learning with Algorithm Distillation


Oct 25, 2022
Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

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Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity


Oct 08, 2021
Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi

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Introducing Symmetries to Black Box Meta Reinforcement Learning


Sep 22, 2021
Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram Friesen, Junhyuk Oh, Yutian Chen

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Discovery of Options via Meta-Learned Subgoals


Feb 12, 2021
Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh

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Balancing Constraints and Rewards with Meta-Gradient D4PG


Oct 13, 2020
Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy Mann

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Discovering Reinforcement Learning Algorithms


Jul 17, 2020
Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver

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Meta-Gradient Reinforcement Learning with an Objective Discovered Online


Jul 16, 2020
Zhongwen Xu, Hado van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver

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Self-Tuning Deep Reinforcement Learning


Mar 02, 2020
Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

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What Can Learned Intrinsic Rewards Capture?


Dec 11, 2019
Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh

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Discovery of Useful Questions as Auxiliary Tasks


Sep 10, 2019
Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

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