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复杂网络上的交互发现过程。

Interacting Discovery Processes on Complex Networks.

机构信息

School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom.

Centre for Advanced Spatial Analysis, University College London, London W1T 4TJ, United Kingdom.

出版信息

Phys Rev Lett. 2020 Dec 11;125(24):248301. doi: 10.1103/PhysRevLett.125.248301.

Abstract

Innovation is the driving force of human progress. Recent urn models reproduce well the dynamics through which the discovery of a novelty may trigger further ones, in an expanding space of opportunities, but neglect the effects of social interactions. Here we focus on the mechanisms of collective exploration, and we propose a model in which many urns, representing different explorers, are coupled through the links of a social network and exploit opportunities coming from their contacts. We study different network structures showing, both analytically and numerically, that the pace of discovery of an explorer depends on its centrality in the social network. Our model sheds light on the role that social structures play in discovery processes.

摘要

创新是人类进步的动力。最近的 urn 模型很好地再现了通过发现新奇事物可能在机会不断扩大的空间中引发更多发现的动态,但忽略了社会互动的影响。在这里,我们专注于集体探索的机制,并提出了一个模型,其中许多 urn 代表不同的探索者,通过社交网络的链接耦合在一起,并利用来自他们联系人的机会。我们研究了不同的网络结构,从理论和数值上表明,探索者发现的速度取决于其在社交网络中的中心度。我们的模型揭示了社会结构在发现过程中所扮演的角色。

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