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Perceiver IO: A General Architecture for Structured Inputs & Outputs


Aug 02, 2021
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira

* Code: https://dpmd.ai/perceiver-code 

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Stabilizing Transformers for Reinforcement Learning


Oct 13, 2019
Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell


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V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control


Sep 26, 2019
H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin Riedmiller, Matthew M. Botvinick

* * equal contribution 

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Learned human-agent decision-making, communication and joint action in a virtual reality environment


May 07, 2019
Patrick M. Pilarski, Andrew Butcher, Michael Johanson, Matthew M. Botvinick, Andrew Bolt, Adam S. R. Parker

* 5 pages, 3 figures. Accepted to The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making, July 7-10, 2019, McGill University, Montreal, Quebec, Canada 

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Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents


Feb 04, 2018
Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran, David Amos, Charles Beattie, Keith Anderson, Antonio García Castañeda, Manuel Sanchez, Simon Green, Audrunas Gruslys, Shane Legg, Demis Hassabis, Matthew M. Botvinick

* 28 pages, 11 figures 

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Structure Learning in Motor Control:A Deep Reinforcement Learning Model


Jul 13, 2017
Ari Weinstein, Matthew M. Botvinick

* 39th Annual Meeting of the Cognitive Science Society, to appear 

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