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In recent years, a proliferation of methods were developed for cooperative multi-agent reinforcement learning (c-MARL).
A taxonomy for swarm robots
Gregory Dudek, Michael Jenkin, Evangelos Milios, and David Wilkes · 1993
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Anh Nguyen, Jason Yosinski, and Jeff Clune · 2015
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Adversarial examples in the physical world, 2016
Alexey Kurakin, Ian Goodfellow, Samy Bengio, et al · 2016
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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A concise introduction to decentralized POMDPs
Frans A Oliehoek and Christopher Amato · 2016
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The limitations of deep learning in adversarial settings
Nicolas Papernot, Patrick McDaniel, Somesh Jha, Matt Fredrikson, Z Berkay Celik, and Ananthram Swami · 2016
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Adversarial attacks on neural network policies
Sandy Huang, Nicolas Papernot, Ian Goodfellow, Yan Duan, and Pieter Abbeel · 2017
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang · 2017
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Delving into adversarial attacks on deep policies
Jernej Kos and Dawn Song · 2017
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Tactics of adversarial attack on deep reinforcement learning agents
Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, and Min Sun · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Multi-agent actor-critic for mixed cooperative-competitive environments
Toward evaluating robustness of deep reinforcement learning with continuous control
Tsui-Wei Weng, Krishnamurthy Dj Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, and Pushmeet Kohli · 2019
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Multi-agent mujoco
C. S. de Witt · 2020
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Is bert really robust? a strong baseline for natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits · 2020
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On the robustness of cooperative multi-agent reinforcement learning
Jieyu Lin, Kristina Dzeparoska, Sai Qian Zhang, Alberto Leon-Garcia, and Nicolas Papernot · 2020
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Facmac: Factored multi-agent centralised policy gradients
Bei Peng, Tabish Rashid, Christian A Schroeder de Witt, Pierre-Alexandre Kamienny, Philip HS Torr, Wendelin Böhmer, and Shimon Whiteson · 2020
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Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, and Igor Mordatch · 2017
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Emergence of grounded compositional language in multi-agent populations
Igor Mordatch and Pieter Abbeel · 2017
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Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang · 2018
Cited alongside, same era.
Adversarial policies: Attacking deep reinforcement learning
Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, and Stuart Russell · 2019
Cited alongside, same era.
A review of cooperative multi-agent deep reinforcement learning
Afshin OroojlooyJadid and Davood Hajinezhad · 2019
Cited alongside, same era.
The StarCraft Multi-Agent Challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philiph H. S. Torr, Jakob Foerster, and Shimon Whiteson · 2019
Cited alongside, same era.
Adversarial attacks on deep-learning models in natural language processing: A survey
Wei Emma Zhang, Quan Z Sheng, Ahoud Alhazmi, and Chenliang Li · 2020
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Adversarial attacks on heterogeneous multi-agent deep reinforcement learning system with time-delayed data transmission
Neshat Elhami Fard and Rastko R Selmic · 2022
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Towards comprehensive testing on the robustness of cooperative multi-agent reinforcement learning
Jun Guo, Yonghong Chen, Yihang Hao, Zixin Yin, Yin Yu, and Simin Li · 2022
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Sparse adversarial attack in multi-agent reinforcement learning
Yizheng Hu and Zhihua Zhang · 2022
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