# Chinese researchers develop Light Society to simulate 1 billion AI characters > Source: > Published: 2026-08-10 16:01:50+00:00 Photo: Yana Iskayeva / sciencefocus.com # Chinese researchers develop Light Society to simulate 1 billion AI characters A team from China's top universities built a framework that can model opinion diffusion and trust dynamics across planetary-scale populations of AI agents A team of Chinese researchers has built a framework called Light Society that can simulate societies of over one billion AI agents, each equipped with realistic demographic profiles and the ability to exhibit human-like social behaviors. The project, detailed in a paper submitted to arXiv, represents a roughly 100x leap over previous agent-based simulations, which typically hit a wall at around 10 million agents due to computational bottlenecks. ## How you simulate a billion people The research team spans some of China’s most elite institutions: the University of Science and Technology of China, Tsinghua University, and Fudan University. Lead researchers Haoxiang Guan and Tie-Yan Liu designed Light Society around two core technical innovations that make billion-scale simulation feasible. The first is a mixture-of-models engine, which essentially distributes the cognitive workload across multiple AI model types rather than routing every agent decision through a single massive language model. The second innovation involves knowledge-distilled surrogate models. In plain terms, the system trains smaller, faster models to mimic the behavior of larger, more sophisticated ones. This lets the framework maintain realistic behavioral fidelity without requiring the computational resources that would normally make billion-agent simulations impossible. Each simulated agent is instantiated with realistic profiles drawn from the World Values Survey, specifically Wave 7 of the long-running global research project. That survey covers beliefs, values, and demographic characteristics across dozens of countries, giving each simulated person a grounded identity rather than a randomly assigned one. ## Trust games at civilizational scale The researchers ran two flagship experiments to demonstrate Light Society’s capabilities. The first was a series of Trust Games, a classic setup from behavioral economics where participants decide how much money to send to a stranger, knowing the stranger can either reciprocate or pocket the cash. Running this across a billion-node network reveals patterns of cooperation and defection that simply can’t emerge in smaller simulations. The second experiment focused on opinion diffusion, essentially modeling how ideas, beliefs, and sentiments propagate through massive social networks. The original source material explicitly notes that Light Society can be used to test methods of influencing public opinion. ## What makes this different from earlier simulations Agent-based modeling has been around for decades. Researchers have used it to study traffic patterns, disease transmission, and market behavior. But these models historically relied on simple rule-based agents following predetermined scripts. The integration of large language models into agent-based simulation is a relatively recent development. LLM-powered agents can engage in nuanced decision-making, adapt to novel situations, and produce emergent behaviors. Earlier LLM-based social simulations topped out at roughly 10 million agents before the compute costs became prohibitive. Light Society’s architectural choices, particularly the surrogate model approach, effectively broke through that ceiling by two orders of magnitude. The researchers have positioned this as enabling earth-scale “in silico” experiments, signaling an ambitious vision: using simulation as a laboratory for understanding human civilization itself. **Disclosure:** This article was edited by Editorial Team. For more information on how we create and review content, see our [Editorial Policy](https://cryptobriefing.com/editorial-policy/).