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Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot


Jul 14, 2021
Joel Z. Leibo, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel

* In International Conference on Machine Learning 2021 (pp. 6187-6199). PMLR 
* Accepted to ICML 2021 and presented as a long talk; 33 pages; 9 figures 

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Learning to Incentivize Other Learning Agents


Jun 10, 2020
Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes, Hongyuan Zha

* 19 pages, 11 figures 

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Malthusian Reinforcement Learning


Dec 17, 2018
Joel Z. Leibo, Julien Perolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel

* 9 pages, 2 tables, 4 figures 

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Value-Decomposition Networks For Cooperative Multi-Agent Learning


Jun 16, 2017
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinicius Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel


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Deep Reinforcement Learning in Large Discrete Action Spaces


Apr 04, 2016
Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, Ben Coppin


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Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions


Dec 16, 2015
Peter Sunehag, Richard Evans, Gabriel Dulac-Arnold, Yori Zwols, Daniel Visentin, Ben Coppin


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The Sample-Complexity of General Reinforcement Learning


Aug 22, 2013
Tor Lattimore, Marcus Hutter, Peter Sunehag

* 16 pages 

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On Nicod's Condition, Rules of Induction and the Raven Paradox


Jul 16, 2013
Hadi Mohasel Afshar, Peter Sunehag

* On raven paradox, Nicod's condition, projectability, induction 

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Concentration and Confidence for Discrete Bayesian Sequence Predictors


Jun 29, 2013
Tor Lattimore, Marcus Hutter, Peter Sunehag

* 17 pages 

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Optimistic Agents are Asymptotically Optimal


Sep 29, 2012
Peter Sunehag, Marcus Hutter

* Proc. 25th Australasian Joint Conference on Artificial Intelligence (AusAI 2012) 15-26 
* 13 LaTeX pages 

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Adaptive Context Tree Weighting


Jan 10, 2012
Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag

* 11 LaTeX pages, 7 tables 

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Principles of Solomonoff Induction and AIXI


Nov 25, 2011
Peter Sunehag, Marcus Hutter

* Proc. Solomonoff 85th Memorial Conference (SOL 2011) pages 386-398 
* 14 LaTeX pages 

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Feature Reinforcement Learning In Practice


Aug 18, 2011
Phuong Nguyen, Peter Sunehag, Marcus Hutter


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Axioms for Rational Reinforcement Learning


Jul 27, 2011
Peter Sunehag, Marcus Hutter

* Proc. 22nd International Conf. on Algorithmic Learning Theory (ALT-2011) pages 338-352 
* 16 LaTeX pages 

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Consistency of Feature Markov Processes


Jul 13, 2010
Peter Sunehag, Marcus Hutter

* Proc. 21st International Conf. on Algorithmic Learning Theory (ALT-2010) pages 360-374 
* 16 LaTeX pages 

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