On Economic Self-Organization Studies: Generation Mechanisms, Evolutionary Dynamics, and Systemic Emergence of Decentralized Order

Engineering notes

Key topics: autonomous driving, planning, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Traditional mainstream economics has long relied on the neoclassical paradigm, assuming that economic systems reside in or gravitate toward static equilibrium guided by central coordination or a Walrasian auctioneer. However, real-world markets, industries, enterprises, and socio-economic networks are fundamentally complex adaptive systems composed of a multitude of autonomous decision-making agents. This paper systematically constructs a theoretical framework for "Economic Self-Organization Studies" to examine how economic systems spontaneously generate macro-order, structural patterns, and functional properties without central control, administrative commands, or centralized planning, relying solely on local non-linear interactions among micro-agents. The paper integrates dissipative structure theory, synergetics, hypercycle theory, and evolutionary economics into a unified economic analytical model. We rigorously formulate the thermodynamic conditions of non-equilibrium states, where an open economic system absorbs negative entropy flow d S_e to counteract internal entropy production d S_i (satisfying d S = d S_e + d S_i < 0), thus driving the system toward higher structural organization. Utilizing Haken's slaving principle, we demonstrate how short-term micro-fluctuations (fast variables) are governed by long-term macroeconomic rules and standards (slow variables/order parameters slow_u). Furthermore, we model how local fluctuations delta_x(t) are amplified through non-linear positive feedback when control parameters cross critical bifurcation thresholds lambda_c, while negative feedback provides systemic stabilization. This theoretical framework elucidates the spontaneous formation of spatial industrial clusters via reaction-diffusion mechanisms, price emergence in decentralized continuous double auctions and automated market maker (AMM) algorithms, network topology evolution driven by preferential attachment, and organizational self-governance in Decentralized Autonomous Organizations (DAOs). Finally, the study highlights a shift in policy paradigm from traditional top-down "command and control" to "evolutionary steering," where policymakers focus on shaping system openness, inducing order parameters, and constructing safety guardrails. Ultimately, this research provides a novel dynamical methodology for understanding decentralized market operations and resilient economic system design in an increasingly complex world.

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