Economic Complex Adaptology: Evolutionary Mechanisms of Self-Reorganization in Complex Adaptive Economic Systems under Uncertainty and Dynamic Competition

Traditional mainstream economics has long relied on equilibrium analysis and the assumption of rational actors, simplifying the economic system into a mechanical system with deterministic solutions obtainable through linear equations. However, the high degree of uncertainty, nonlinear mutations, endogenous crises, and continuous emergence of innovations exhibited in real-world economic operations have profoundly exposed the explanatory limitations of the traditional equilibrium paradigm. This paper systematically elucidates and constructs the theoretical system and analytical framework of "Economic Complex Adaptology." This discipline views the economic system as a complex adaptive system (CAS) composed of a massive number of micro-agents with active learning and adaptive capabilities. This paper delves into the rule evolution, information processing, and trial-and-error mechanisms of micro-agents in a dynamic competitive environment, elucidating how micro-interactions "emerge" into complex structures and orders at the macro level through nonlinear positive and negative feedback mechanisms. Furthermore, it analyzes the intrinsic mechanisms of self-reorganization, topological network reconstruction, and resilient evolution of the system in the face of external shocks and endogenous disturbances. Research shows that the long-term evolution of the economic system does not converge to a single static equilibrium, but rather exists in a state of continuous adaptive reconstruction on the "edge of chaos" driven by uncertainty and dynamic competition. Based on this, this paper proposes an adaptive governance and resilience policy design approach for complex economic systems, providing a new perspective and paradigm tool for solving practical problems such as macroeconomic fluctuations, industrial ecosystem evolution, and financial risk transmission.