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Picture for Shixiang Shane Gu

Identifying Co-Adaptation of Algorithmic and Implementational Innovations in Deep Reinforcement Learning: A Taxonomy and Case Study of Inference-based Algorithms


Mar 31, 2021
Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu

* The implementation is available at: https://github.com/frt03/inference-based-rl 

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Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning


Mar 23, 2021
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu


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Human-centric Dialog Training via Offline Reinforcement Learning


Oct 12, 2020
Natasha Jaques, Judy Hanwen Shen, Asma Ghandeharioun, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Shane Gu, Rosalind Picard

* To appear in EMNLP 2020 (long paper) 

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EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL


Jul 21, 2020
Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu


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