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Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency

Dec 11, 2021
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson

* AAAI 2022 

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Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning

Jul 30, 2021
Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann

* To Appear in Uncertainty in Artificial Intelligence (UAI) 2021. 10 figures, 14 pages 

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Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation

May 20, 2021
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann

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The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors

Jan 26, 2021
William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals

* 37 pages, initial submission, accepted at NeurIPS. arXiv admin note: substantial text overlap with arXiv:1904.10079 

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Evaluating the Robustness of Collaborative Agents

Jan 14, 2021
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, A. D. Dragan, Rohin Shah

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Deep Interactive Bayesian Reinforcement Learning via Meta-Learning

Jan 11, 2021
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann

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Difference Rewards Policy Gradients

Dec 21, 2020
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani

* This work as been accepted as an Extended Abstract in Proc. of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), U. Endriss, A. Now\'e, F. Dignum, A. Lomuscio (eds.), May 3-7 2021, Online 

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"It's Unwieldy and It Takes a Lot of Time." Challenges and Opportunities for Creating Agents in Commercial Games

Sep 01, 2020
Mikhail Jacob, Sam Devlin, Katja Hofmann

* 7 pages, 3 figures, to be published in the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-20) 

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Meta-Learning for Variational Inference

Jul 06, 2020
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

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Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control

Jun 15, 2020
Rika Antonova, Maksim Maydanskiy, Danica Kragic, Sam Devlin, Katja Hofmann

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A Comparison of Self-Play Algorithms Under a Generalized Framework

Jun 08, 2020
Daniel Hernandez, Kevin Denamganai, Sam Devlin, Spyridon Samothrakis, James Alfred Walker

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Rolling Horizon Evolutionary Algorithms for General Video Game Playing

Mar 27, 2020
Raluca D. Gaina, Sam Devlin, Simon M. Lucas, Diego Perez-Liebana

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Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

Oct 28, 2019
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann

* Published at Neurips 2019 

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Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems

Mar 13, 2019
Kleanthis Malialis, Sam Devlin, Daniel Kudenko

* Keywords: congestion problems, resource management, multiagent reinforcement learning, multiagent systems, multiagent learning, resource abstraction. In Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems (AAMAS '16) 

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The Multi-Agent Reinforcement Learning in MalmĂ– (MARLĂ–) Competition

Jan 23, 2019
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, Andre Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita

* Challenges in Machine Learning (NIPS Workshop), 2018 
* 2 pages plus references 

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The Text-Based Adventure AI Competition

Oct 19, 2018
Timothy Atkinson, Hendrik Baier, Tara Copplestone, Sam Devlin, Jerry Swan

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Win Prediction in Esports: Mixed-Rank Match Prediction in Multi-player Online Battle Arena Games

Nov 17, 2017
Victoria Hodge, Sam Devlin, Nick Sephton, Florian Block, Anders Drachen, Peter Cowling

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