英文标题：
《A Theory of Updating Ambiguous Information》
---
作者：
Rui Tang
---
最新提交年份：
2020
---
英文摘要：
  We introduce a new updating rule, the conditional maximum likelihood rule (CML) for updating ambiguous information. The CML formula replaces the likelihood term in Bayes\' rule with the maximal likelihood of the given signal conditional on the state. We show that CML satisfies a new axiom, increased sensitivity after updating, while other updating rules do not. With CML, a decision maker\'s posterior is unaffected by the order in which independent signals arrive. CML also accommodates recent experimental findings on updating signals of unknown accuracy and has simple predictions on learning with such signals. We show that an information designer can almost achieve her maximal payoff with a suitable ambiguous information structure whenever the agent updates according to CML.
---
中文摘要：
我们引入了一种新的更新规则——条件最大似然规则（CML），用于更新模糊信息。CML公式将贝叶斯规则中的似然项替换为给定信号在状态条件下的最大似然项。我们证明了CML满足一个新的公理，即更新后灵敏度增加，而其他更新规则则不满足。对于慢性粒细胞白血病，决策者的后验概率不受独立信号到达顺序的影响。CML还提供了更新未知准确度信号的最新实验结果，并对使用此类信号进行学习进行了简单预测。我们证明，每当代理根据CML进行更新时，信息设计师几乎可以通过适当的模糊信息结构实现最大回报。
---
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。
--

---
PDF下载：
-->