Stochastic bounded confidence opinion dynamics

F. Baccelli, Avhishek Chatterjee, S. Vishwanath
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引用次数: 13

Abstract

In a vast body of opinion dynamics literature, an agent updates its opinion based on the opinions of its neighbors in a static social graph, regardless of their differences in opinions. In contrast, the bounded confidence opinion dynamics does not presume a static interaction graph, and instead limits interactions to those agents that share related opinions (i.e., whose opinions are close to one another). We generalize the bounded confidence opinion dynamics model by incorporating stochastic interactions based on opinion differences and the endogenous evolution of the agent opinions, which itself is a random process. We analytically characterize the conditions under which this stochastic dynamics is stable in an appropriate sense.
随机有界置信度意见动力学
在大量的意见动态文献中,一个代理根据静态社交图中邻居的意见更新自己的意见,而不管他们的意见不同。相比之下,有限置信度意见动态并不假设一个静态的交互图,而是将交互限制在那些共享相关意见的代理(即,他们的意见彼此接近)。将基于意见差异的随机交互作用和代理意见内生进化的随机过程结合起来,对有界置信度意见动力学模型进行了推广。我们解析地描述了这种随机动力学在适当意义上稳定的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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