摘要翻译:
我们考虑了一大类社会学习模型,其中一组主体面对关于世界状态的不确定性,共享相同的效用函数,观察私人信号,并在一般的动态环境中进行交互。我们引入了社会学习均衡,这是一个静态均衡概念,它从给定的广泛形式的细节中抽象出来,但却捕捉到了相应的渐近均衡行为。我们建立了均衡状态下协议、羊群和信息聚集的一般条件,突出了协议和信息聚集之间的联系。
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英文标题:
《Social learning equilibria》
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作者:
Elchanan Mossel, Manuel Mueller-Frank, Allan Sly and Omer Tamuz
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最新提交年份:
2019
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分类信息:
一级分类:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、
数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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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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一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
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英文摘要:
We consider a large class of social learning models in which a group of agents face uncertainty regarding a state of the world, share the same utility function, observe private signals, and interact in a general dynamic setting. We introduce Social Learning Equilibria, a static equilibrium concept that abstracts away from the details of the given extensive form, but nevertheless captures the corresponding asymptotic equilibrium behavior. We establish general conditions for agreement, herding, and information aggregation in equilibrium, highlighting a connection between agreement and information aggregation.
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PDF链接:
https://arxiv.org/pdf/1207.5895