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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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Generative Adversarial Self-Imitation Learning


Dec 03, 2018
Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee


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Contingency-Aware Exploration in Reinforcement Learning


Nov 05, 2018
Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee

* Preprint, work in progress. Under review at ICLR 2019 

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Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies


Nov 02, 2018
Sungryull Sohn, Junhyuk Oh, Honglak Lee

* In 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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Many-Goals Reinforcement Learning


Jun 22, 2018
Vivek Veeriah, Junhyuk Oh, Satinder Singh


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On Learning Intrinsic Rewards for Policy Gradient Methods


Jun 22, 2018
Zeyu Zheng, Junhyuk Oh, Satinder Singh


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Self-Imitation Learning


Jun 14, 2018
Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee


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Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning


Nov 07, 2017
Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli

* ICML 2017 

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Value Prediction Network


Nov 06, 2017
Junhyuk Oh, Satinder Singh, Honglak Lee

* NIPS 2017 

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Control of Memory, Active Perception, and Action in Minecraft


May 30, 2016
Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee

* ICML 2016 

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Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network


Dec 24, 2015
Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee


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Action-Conditional Video Prediction using Deep Networks in Atari Games


Dec 22, 2015
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard Lewis, Satinder Singh

* Published at NIPS 2015 (Advances in Neural Information Processing Systems 28) 

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