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MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning


May 25, 2022
Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles Kamhoua, Evangelos E. Papalexakis, Fei Fang

* 25 pages 

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Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers


Apr 28, 2022
Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin


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Retrospective on the 2021 BASALT Competition on Learning from Human Feedback


Apr 14, 2022
Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Chan Jun Shern, Daniel del Castillo, Tom Lieberum

* Accepted to the PMLR NeurIPS 2021 Demo & Competition Track volume 

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MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned


Feb 17, 2022
Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman

* Under review for PMLR volume on NeurIPS 2021 competitions 

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A Survey of Explainable Reinforcement Learning


Feb 17, 2022
Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang


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The MineRL BASALT Competition on Learning from Human Feedback


Jul 05, 2021
Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca Dragan

* NeurIPS 2021 Competition Track 

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Towards robust and domain agnostic reinforcement learning competitions


Jun 07, 2021
William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

* 20 pages, several figures, published PMLR 

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Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods


Feb 25, 2021
Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso


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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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Guaranteeing Reproducibility in Deep Learning Competitions


May 12, 2020
Brandon Houghton, Stephanie Milani, Nicholay Topin, William Guss, Katja Hofmann, Diego Perez-Liebana, Manuela Veloso, Ruslan Salakhutdinov

* Accepted as a poster presentation to the 2019 NeruIPS Challenges in Machine Learning workshop (CiML) 

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