摘要
随着生成式人工智能(AI)的突破性进展,计算经济学正经历从传统数值模拟仿真向AI驱动新范式的转型。作为经济学与计算机科学的交叉学科,计算经济学融合了数值计算、基于主体的建模以及机器学习等多学科技术方法,呈现出显著的方法论多元化特征。该学科的发展历程可划分为三个主要阶段:早期以均衡理论数值计算为特征,中期以复杂系统仿真为核心,当前则进入与人工智能深度融合的新阶段。AI技术尤其是基于深度学习的大模型显著扩大了经济系统的可计算边界,在数据生成机制、研究对象范畴以及研究方法体系等方面带来革命性创新,推进了理论驱动与数据驱动研究范式的有机融合,形成“知识自生成”的新模式。尽管当前AI与计算经济学的交叉融合仍处于初级阶段,但其必将对计算经济学的学科定位和研究范式产生深远影响。
With the breakthrough advances in generative artificial intelligence (AI), computational economics is undergoing a transformation from traditional numerical simulation and modeling toward an AI-driven paradigm. As an interdisciplinary field bridging economics and computer science, computational economics integrates numerical computation, agent-based modeling, and machine learning, exhibiting pronounced methodological diversity. Its development can be divided into three major stages: an early stage characterized by numerical computation of equilibrium theory, a middle stage centered on complex system simulation, and the current stage marked by deep integration with AI. AI technologies-particularly large language models based on deep learning-have significantly expanded the computational frontier of economic systems, bringing revolutionary innovations to data generation mechanisms, research domains, and methodological frameworks. This shift fosters an organic synthesis of theory-driven and data-driven paradigms, giving rise to a new mode of “self-generating knowledge”. Although the intersection of AI and computational economics is still in its early stages, it is likely to exert a profound impact on the discipline’s orientation and research paradigm.
出处
《学海》
北大核心
2025年第5期146-153,216,共9页
Academia Bimestris
