General Automatic Solution Generation for Social Problems

doi:10.1007/s11633-024-1496-2

2025-01-24

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DOI：10.1007/s11633-024-1496-2

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摘要

En 中文

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 the 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 built upon agent-based models that enables 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 functional viability. To demonstrate the effectiveness of the 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 nonprofit purposes. This study demonstrated that ASOS provides an efficient and systematic approach for generating solutions for enhancing our society.

Keyword:

General automatic generation

global-local regulation

hypergraph social representation

symbolic hybrid scheme

generalized operation protocol