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

Japanese

このようなコミュニティーワールドネットワークの構造とダイナミクスは密接に関連しています。これらのシステムを統計的に特徴づけるための膨大なフレームワークの進歩にもかかわらず、特定のメソシカル構造がなぜ出現するのかを説明する一般的なメソシカルフレームワークは未だに難解です。ここでは、ゲームグラフのバランスを導入し、パイオフを駆動したパートナー選択の安定した休息ポイント、およびナッシュバランスの2つのコアのダイナミクスです。これは、戦略的相互作用の化石化された記録としてのネットワーク構造を明らかにします。さらに、我々の2種類の複雑なゲームが正確に4つのネットワークトポロジーを持っていることを分析的に証明します

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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