Optimal Influence Under Observational Learning

Nikolas Tsakas
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引用次数: 3

Abstract

We study the optimal targeting problem of a firm that seeks to maximize the diffusion of a product in a society where agents learn from their neighbors. The firm can seed the product to a subset of the population and our goal is to find which is the optimal subset to target. We provide a condition that characterizes the optimal targeting strategy for any network structure. The key parameter in this condition is the agents' decay centrality, which takes into account how close an agent is to others, in a way that distant agents are weighted less than closer ones.
观察学习下的最优影响
我们研究了一个企业的最优目标问题,该问题寻求在一个代理人向邻居学习的社会中最大化产品的扩散。公司可以将产品投放到人口的一个子集,我们的目标是找出哪个是最优的目标子集。我们提供了表征任何网络结构的最优目标策略的条件。这种情况下的关键参数是代理的衰减中心性,它考虑了代理与其他代理的接近程度,在某种程度上,距离远的代理的权重小于距离近的代理。
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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