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GrASP: Gradient-Based Affordance Selection for Planning


Feb 08, 2022
Vivek Veeriah, Zeyu Zheng, Richard Lewis, Satinder Singh


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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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Learning State Representations from Random Deep Action-conditional Predictions


Feb 09, 2021
Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard Lewis, Satinder Singh


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Learning Retrospective Knowledge with Reverse Reinforcement Learning


Jul 09, 2020
Shangtong Zhang, Vivek Veeriah, Shimon Whiteson


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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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How Should an Agent Practice?


Dec 15, 2019
Janarthanan Rajendran, Richard Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh

* AAAI-2020 

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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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Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning


Mar 08, 2019
Alex Kearney, Vivek Veeriah, Jaden Travnik, Patrick M. Pilarski, Richard S. Sutton


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Many-Goals Reinforcement Learning


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


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