摘要翻译：
我们介绍并研究了一个罕见相互作用的长期约定形成模型。这个模型中的参与者通过观察过去互动的最近加权样本来形成信念，他们对此做出最好的反应。我们提出了一个连续状态马尔可夫模型，非常适合我们的环境，并开发了一种方法，与更大类类似的学习模型相关。我们证明了该模型存在一个唯一的渐近分布，它的质量集中在一些最小的路由块构型上。与已有的关于长期约定形成的文献相比，我们着重研究了最小限制块内的行为，并给出了在最小限制块内收敛到（近似）混合均衡约定的条件。
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英文标题：
《Stochastic Stability of a Recency Weighted Sampling Dynamic》
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作者：
Alexander Aurell and Gustav Karreskog
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最新提交年份：
2021
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分类信息：

一级分类：Economics        经济学
二级分类：Theoretical Economics        理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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英文摘要：
  We introduce and study a model of long-run convention formation for rare interactions. Players in this model form beliefs by observing a recency-weighted sample of past interactions, to which they noisily best respond. We propose a continuous state Markov model, well-suited for our setting, and develop a methodology that is relevant for a larger class of similar learning models. We show that the model admits a unique asymptotic distribution which concentrates its mass on some minimal CURB block configuration. In contrast to existing literature of long-run convention formation, we focus on behavior inside minimal CURB blocks and provide conditions for convergence to (approximate) mixed equilibria conventions inside minimal CURB blocks.
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PDF链接：
https://arxiv.org/pdf/2009.12910