论文标题
建模多代理系统中的异质结果
Modelling heterogeneous outcomes in multi-agent systems
论文作者
论文摘要
在社会，经济和机器行为研究中，可以将一系列广泛的经验现象建模为具有平均动态的复杂系统。但是，其中许多模型自然会导致共识或共识样结果。实际上，经验现象很少融合到这些现象，而是具有代理状态的丰富，持续变化的特征。这种异质结果是许多模型的自然结果，这些模型将外部扰动纳入了代理的原本凸动力学。本文的目的是形式化异质性的概念，并证明哪些类别的模型能够作为结果实现，因此更适合对重要的经验问题进行建模。我们通过确定（时变）相互作用网络的拓扑限制了代理可能的稳态结果的空间，以及与图表上随机步行的研究如何相关。我们考虑了许多有意的示例，以证明如何应用结果。
A broad set of empirical phenomenon in the study of social, economic and machine behaviour can be modelled as complex systems with averaging dynamics. However many of these models naturally result in consensus or consensus-like outcomes. In reality, empirical phenomenon rarely converge to these and instead are characterized by rich, persistent variation in the agent states. Such heterogeneous outcomes are a natural consequence of a number of models that incorporate external perturbation to the otherwise convex dynamics of the agents. The purpose of this paper is to formalize the notion of heterogeneity and demonstrate which classes of models are able to achieve it as an outcome, and therefore are better suited to modelling important empirical questions. We do so by determining how the topology of (time-varying) interaction networks restrict the space of possible steady-state outcomes for agents, and how this is related to the study of random walks on graphs. We consider a number of intentionally diverse examples to demonstrate how the results can be applied.
