Potential challenges. While scaling up the number of agents can lead to improved task efficiency
and enhance the realism and credibility of social simulations [22; 109; 520], there are several
challenges ahead of us. For example, the computational burden will increase with the large number
of deployed AI agents, calling for better architectural design and computational optimization to
ensure the smooth running of the entire system. For example, as the number of agents increases, the
challenges of communication and message propagation become quite formidable. This is because the
communication network of the entire system becomes highly complex. As previously mentioned in §
5.3.3, in multi-agent systems or societies, there can be biases in information dissemination caused
by hallucinations, misunderstandings, and the like, leading to distorted information propagation. A
system with more agents could amplify this risk, making communication and information exchange
TheRiseandPotentialofLargeLanguageModel BasedAgents