The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These systems pose novel and under-explored risks. In this report, we provide a structured taxonomy of these risks by identifying three key failure modes (miscoordination, conflict, and collusion) based on agents' incentives, as well as seven key risk factors (information asymmetries, network effects, selection pressures, destabilising dynamics, commitment problems, emergent agency, and multi-agent security) that can underpin them. We highlight several important instances of each risk, as well as promising directions to help mitigate them. By anchoring our analysis in a range of real-world examples and experimental evidence, we illustrate the distinct challenges posed by multi-agent systems and their implications for the safety, governance, and ethics of advanced AI.

本研究探讨了高级人工智能智能体的快速发展所带来的多智能体系统的新颖风险。通过识别不协调、冲突和共谋三种关键失效模式，以及信息不对称等七个主要风险因素，论文提出了一种结构化的风险分类体系，强调了多智能体系统在安全、治理和伦理方面的挑战及其减缓策略的重要性。

高级人工智能带来的多智能体风险