How can enforcement agents improve multi-agent AI safety?
Enforcement Agents: Enhancing Accountability and Resilience in Multi-Agent AI Frameworks
April 8, 2025
https://arxiv.org/pdf/2504.04070This paper introduces "Enforcement Agents" (EAs), AI agents acting as supervisors within a multi-agent system to improve safety and reliability. EAs monitor other agents, detect misbehavior, and intervene in real-time. The research demonstrates, via a simulated drone patrol scenario, that adding EAs increases the system's success rate and lifespan, especially when multiple EAs are deployed. This concept is relevant to LLM-based multi-agent systems because it offers a dynamic, adaptable approach to alignment without relying on fixed rules, potentially improving safety and robustness in complex, evolving multi-agent environments.