人工智能时代宏观经济复杂系统构建

In the era of rapid development of artificial intelligence, a richer data foundation is provided for studying the behaviors of microeconomic entities, and it also enables effective simulation and analysis of complex macroeconomic systems. These systems typically consist of various types of microeconomic entities, including governments, residents, enterprises, financial institutions, and international economies. A core challenge during the simulation process of macroeconomic systems is how to effectively integrate the behaviors and expectations of different economic entities, as these factors generate complex interactions in the market. Due to the role of information transmission, these microeconomic entities, influenced by differing expectations regarding future economic conditions and resource allocation, develop their own trading behaviors, which in turn affect the dynamic changes of the overall market.The construction of an AI macro model is imperative. Firstly, this article introduces the framework, connections, and operational processes of a smart micro-entity macroeconomic system. By constructing a smart micro-entity model to simulate the behavioral logic of various micro-level entities, it aligns the microeconomic logic with reality. Then, utilizing the self-adaptive decisions of these smart micro-entities within the macro framework reveals the operating laws of macroeconomics. Finally, the system undergoes dynamic evolution, model validation, and policy effect analysis.