How do AI agents cooperate under disruptions?
Cooperative Resilience in Artificial Intelligence Multiagent Systems
September 23, 2024
https://arxiv.org/pdf/2409.13187This research proposes a new metric called "cooperative resilience" to measure how well groups of AI agents, including those powered by LLMs, can handle disruptions and still achieve their goals together. The researchers tested this metric in simulations where AI agents, some using reinforcement learning (RL) and others using large language models (LLMs), needed to work together to manage a shared resource. They found that while RL agents generally showed more resilience, both types could sometimes adapt and even improve after disruptions. This highlights that:
- Cooperative resilience is important for understanding how well LLM-based multi-agent systems will perform in real-world scenarios where unexpected events are common.
- Traditional metrics might miss how well these systems can adapt, so using cooperative resilience could be key to building more robust and reliable AI that works well in a team.