2026
Multi-Dimensional Perturbation Strategies for Adversarial Attacks in Multi-Agent Deep Reinforcement Learning
ICRA 2026poster
Research indicates that single-agent reinforcement learning is vulnerable to adversarial attacks, which can lead to decision-making errors. Similarly, multi-agent deep reinforcement learning (MADRL) systems face analogous adversarial threats. However, existing attack methods require substantial inve…