Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning

arXiv 2502.02844 ↗First posted 5 Feb 2025cs.LG cs.AI cs.CRcited by 6

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Abstract (arXiv)

Traditional robust methods in multi-agent reinforcement learning (MARL) often struggle against coordinated adversarial attacks in cooperative scenarios. To address this limitation, we propose the Wolfpack Adversarial Attack framework, inspired by wolf hunting strategies, which targets an initial agent and its assisting agents to disrupt cooperation. Additionally, we introduce the Wolfpack-Adversarial Learning for MARL (WALL) framework, which trains robust MARL policies to defend against the proposed Wolfpack attack by fostering systemwide collaboration. Experimental results underscore the devastating impact of the Wolfpack attack and the significant robustness improvements achieved by WALL. Our code is available at https://github.com/sunwoolee0504/WALL.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 56 of its 83 references that are in the map. First posted on arXiv 5 Feb 2025.

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56 of 83 references.

References · 56

2017Attention Is All You Needcited by 59,932
2014Explaining and Harnessing Adversarial Examplescited by 7,287
2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,528
2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
2019The StarCraft Multi-Agent Challengecited by 589
2019Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithmscited by 555
2017Value-Decomposition Networks For Cooperative Multi-Agent Learningcited by 490
2020Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 475
2017Robust Adversarial Reinforcement Learningcited by 439
2017Safe Model-based Reinforcement Learning with Stability Guaranteescited by 347
2017Adversarial Attacks on Neural Network Policiescited by 314
2020QPLEX: Duplex Dueling Multi-Agent Q-Learningcited by 267

38 more

2020Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observationscited by 235
2020PettingZoo: Gym for Multi-Agent Reinforcement Learningcited by 209
2019Action Robust Reinforcement Learning and Applications in Continuous Controlcited by 167
2017Robust Deep Reinforcement Learning with Adversarial Attackscited by 152
2019A Review of Cooperative Multi-Agent Deep Reinforcement Learningcited by 147
2021Robust Reinforcement Learning on State Observations with Learned Optimal Adversarycited by 133
2022RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learningcited by 115
2020Adaptive Reward-Poisoning Attacks against Reinforcement Learningcited by 86
2022Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexitycited by 85
2018Reinforcement Learning with Perturbed Rewardscited by 76
2019Robust Reinforcement Learning for Continuous Control with Model Misspecificationcited by 76
2020Robust Reinforcement Learning using Adversarial Populationscited by 64
2021Adversarial Attacks On Multi-Agent Communicationcited by 48
2020On the Robustness of Cooperative Multi-Agent Reinforcement Learningcited by 39
2023Robust Multi-Agent Reinforcement Learning with State Uncertaintycited by 35
2023Adversarial Model for Offline Reinforcement Learningcited by 31
2020Robustifying Reinforcement Learning Agents via Action Space Adversarial Trainingcited by 30
2021A Max-Min Entropy Framework for Reinforcement Learningcited by 28
2021Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environmentscited by 26
2022Robust Imitation Learning against Variations in Environment Dynamicscited by 26
2022Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Controlcited by 25
2023Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithmscited by 25
2024Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertaintycited by 24
2020Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learningcited by 23
2022Towards Comprehensive Testing on the Robustness of Cooperative Multi-agent Reinforcement Learningcited by 21
2022What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?cited by 21
2023Towards Minimax Optimality of Model-based Robust Reinforcement Learningcited by 21
2021Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learningcited by 18
2023Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Gamecited by 18
2023Distributionally Robust Model-based Reinforcement Learning with Large State Spacescited by 17
2022RoMFAC: A robust mean-field actor-critic reinforcement learning against adversarial perturbations on statescited by 16
2020Query-based Targeted Action-Space Adversarial Policies on Deep Reinforcement Learning Agentscited by 15
2023Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackerscited by 15
2021Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learningcited by 14
2021Understanding Adversarial Attacks on Observations in Deep Reinforcement Learningcited by 13
2024Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruptioncited by 12
2022Efficient Reward Poisoning Attacks on Online Deep Reinforcement Learningcited by 9
2024Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Spacecited by 9

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Citing papers per year: 2025: 2; 2026: 4.

6 papers.