Adversarial Attacks On Multi-Agent Communication

Understand

Growing at a fast pace, modern autonomous systems will soon be deployed at scale, opening up the possibility for cooperative multi-agent systems.

• Sharing information and distributing workloads allow autonomous agents to better perform tasks and increase computation efficiency.
• However, shared information can be modified to execute adversarial attacks on deep learning models that are widely employed in modern systems.
• Thus, we aim to study the robustness of such systems and focus on exploring adversarial attacks in a novel multi-agent setting where communication is done through sharing learned intermediate representations of neural networks.