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Efficient Querying for Cooperative Probabilistic Commitments

Dec 14, 2020
Qi Zhang, Edmund H. Durfee, Satinder Singh


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The Value Equivalence Principle for Model-Based Reinforcement Learning

Nov 06, 2020
Christopher Grimm, André Barreto, Satinder Singh, David Silver

* NeurIPS-2020 

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Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments

Oct 28, 2020
Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh


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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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Learning to Play No-Press Diplomacy with Best Response Policy Iteration

Jun 17, 2020
Thomas Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach


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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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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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Hindsight Credit Assignment

Dec 05, 2019
Anna Harutyunyan, Will Dabney, Thomas Mesnard, Mohammad Azar, Bilal Piot, Nicolas Heess, Hado van Hasselt, Greg Wayne, Satinder Singh, Doina Precup, Remi Munos

* NeurIPS 2019 

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Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem

Nov 25, 2019
John Holler, Risto Vuorio, Zhiwei Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye

* ICDM 2019 Short Paper 

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Disentangled Cumulants Help Successor Representations Transfer to New Tasks

Nov 25, 2019
Christopher Grimm, Irina Higgins, Andre Barreto, Denis Teplyashin, Markus Wulfmeier, Tim Hertweck, Raia Hadsell, Satinder Singh


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Object-oriented state editing for HRL

Oct 31, 2019
Victor Bapst, Alvaro Sanchez-Gonzalez, Omar Shams, Kimberly Stachenfeld, Peter W. Battaglia, Satinder Singh, Jessica B. Hamrick

* 8 pages; accepted to the Perception as Generative Reasoning workshop of the 33rd Conference on Neural InformationProcessing Systems (NeurIPS 2019) 

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Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles

Oct 23, 2019
Aditya Modi, Nan Jiang, Ambuj Tewari, 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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No Press Diplomacy: Modeling Multi-Agent Gameplay

Sep 04, 2019
Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron Courville

* Accepted at NeurIPS 2019 

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Behaviour Suite for Reinforcement Learning

Aug 13, 2019
Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepezvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt


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Learning Independently-Obtainable Reward Functions

Jan 31, 2019
Christopher Grimm, 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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Learning End-to-End Goal-Oriented Dialog with Multiple Answers

Aug 24, 2018
Janarthanan Rajendran, Jatin Ganhotra, Satinder Singh, Lazaros Polymenakos

* EMNLP 2018. permuted-bAbI dialog tasks are available at - https://github.com/IBM/permuted-bAbI-dialog-tasks 

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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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Named Entities troubling your Neural Methods? Build NE-Table: A neural approach for handling Named Entities

Apr 22, 2018
Janarthanan Rajendran, Jatin Ganhotra, Xiaoxiao Guo, Mo Yu, Satinder Singh


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The Advantage of Doubling: A Deep Reinforcement Learning Approach to Studying the Double Team in the NBA

Mar 08, 2018
Jiaxuan Wang, Ian Fox, Jonathan Skaza, Nick Linck, Satinder Singh, Jenna Wiens

* Accepted to MIT Sloan Sports Analytics 2018. First two authors contributed equally 

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Markov Decision Processes with Continuous Side Information

Nov 15, 2017
Aditya Modi, Nan Jiang, Satinder Singh, Ambuj Tewari


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