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Minqi Jiang

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Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts

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Feb 26, 2024
Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob Foerster, Tim Rocktäschel, Roberta Raileanu

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Refining Minimax Regret for Unsupervised Environment Design

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Feb 19, 2024
Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows, Minqi Jiang, Michael Dennis, Jakob Foerster

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Multi-Agent Diagnostics for Robustness via Illuminated Diversity

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Jan 24, 2024
Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel

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Learning to Act without Actions

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Dec 17, 2023
Dominik Schmidt, Minqi Jiang

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The Generalization Gap in Offline Reinforcement Learning

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Dec 10, 2023
Ishita Mediratta, Qingfei You, Minqi Jiang, Roberta Raileanu

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Learning Curricula in Open-Ended Worlds

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Dec 08, 2023
Minqi Jiang

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minimax: Efficient Baselines for Autocurricula in JAX

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Nov 23, 2023
Minqi Jiang, Michael Dennis, Edward Grefenstette, Tim Rocktäschel

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JaxMARL: Multi-Agent RL Environments in JAX

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Nov 20, 2023
Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Gardar Ingvarsson, Timon Willi, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktaschel, Chris Lu, Jakob Nicolaus Foerster

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Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design

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Oct 04, 2023
Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster

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ADGym: Design Choices for Deep Anomaly Detection

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Sep 27, 2023
Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao

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