Weaponizing Actions in Multi-Agent Reinforcement Learning: Theoretical and Empirical Study on Security and Robustness - researchr publication authors

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Tongtong Liu, Joe McCalmon, Md Asifur Rahman, Cameron Lischke, Talal Halabi, Sarra Alqahtani. Weaponizing Actions in Multi-Agent Reinforcement Learning: Theoretical and Empirical Study on Security and Robustness. In Reyhan Aydogan, Natalia Criado, Jérôme Lang, Víctor Sánchez-Anguix, Marc Serramia, editors, PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Valencia, Spain, November 16-18, 2022, Proceedings. Volume 13753 of Lecture Notes in Computer Science, pages 347-363, Springer, 2022. [doi]

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