Given the escalating intricacy and multifaceted nature of contemporary social
systems, manually generating solutions to address pertinent social issues has
become a formidable task. In response to this challenge, the rapid development
of artificial intelligence has spurred the exploration of computational
methodologies aimed at automatically generating solutions. However, current
methods for auto-generation of solutions mainly concentrate on local social
regulations that pertain to specific scenarios. Here, we report an automatic
social operating system (ASOS) designed for general social solution generation,
which is built upon agent-based models, enabling both global and local analyses
and regulations of social problems across spatial and temporal dimensions. ASOS
adopts a hypergraph with extensible social semantics for a comprehensive and
structured representation of social dynamics. It also incorporates a
generalized protocol for standardized hypergraph operations and a symbolic
hybrid framework that delivers interpretable solutions, yielding a balance
between regulatory efficacy and function viability. To demonstrate the
effectiveness of ASOS, we apply it to the domain of averting extreme events
within international oil futures markets. By generating a new trading role
supplemented by new mechanisms, ASOS can adeptly discern precarious market
conditions and make front-running interventions for non-profit purposes. This
study demonstrates that ASOS provides an efficient and systematic approach for
generating solutions for enhancing our society.

研究报告通过构建基于代理模型的自动社会操作系统（ASOS）的方法，采用超图和符号混合框架来综合和结构化地表示社会动态，以解决当前社会问题生成解决方案的相关挑战，并在国际油期货市场中成功应用 ASOS 来识别潜在市场条件并进行干预，从而提出了一种有效且系统的解决方案生成方法。