Newest papers

Strategic Origins of Network Structure

Christoph Riedl, Rory Smead · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.24792 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

这种共同体网络的机制和动态结构与复杂网络密切相关。尽管在统计上对这些系统的特点取得了巨大的进展,但一般化机制框架解释了为什么具体的中等尺寸结构出现仍然令人难以置信。在这里我们引入了游戏图表平衡,这是一个收益驱动的合作伙伴选择动态的稳定休息点,类似于纳什平衡。这揭示了网络结构作为战略交互的化石记录。我们分析证明,两个类型的游戏有四个网络图表,这些都是其耗尽的热力学阶段:分类,分类和两个核心周边区域。这导致了网络结构作为K$类型的手动交互的总和。此外,我们的四个不同类型的纳什平衡游戏在分析上表现出核心周边形态,但他们的分类表明,在国际刑事

Machine translation (Meta M2M100); the English original follows.

Abstract

The structure and dynamics of complex networks are intimately linked. Despite immense progress in statistically characterizing these systems, a generalized mechanistic framework explaining why specific mesoscale structures emerge remains elusive. Here we introduce the game-graph equilibrium, the stable rest point of a payoff-driven partner-choice dynamic, analogous to a Nash equilibrium. This reveals network structure as the fossilized record of strategic interaction. We prove analytically that two-type games have exactly four network topologies, which are their exhaustive thermodynamic phases: assortative, disassortative, and two core-peripheries. This result generalizes to $K^K$ topological classes for $K$-type interactions. Furthermore, four distinct Nash equilibria produce core-periphery topologies, yet their payoffs reveal whether the underlying dynamic is cooperative or exploitative. To recover the generating dynamics from observed networks, we develop mechanistic inference by constraining a block model to lie on a low-dimensional, game-theoretic manifold. Applied to real-world networks, the model yields interpretable quantities, distinguishes states that look identical to conventional methods, predicts network topologies it has never seen without retraining, and controls its own complexity without hand-tuned penalties. Networks such as international trade are well described by the model despite the hard constraint, suggesting that real-world systems are organized by payoff-driven partner choice. Our framework resolves a foundational ambiguity by offering a precise, mechanistic definition of communities: strategic equivalence.

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Topics: Ambiguity, Nash equilibrium, Computer science, Inference, Network structure, Network formation

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