论文标题

错误的共识,信息理论和预测市场

False Consensus, Information Theory, and Prediction Markets

论文作者

Kong, Yuqing, Schoenebeck, Grant

论文摘要

我们研究一个环境,贝叶斯特工具有共同先验的私人信息与事件的结果有关,并依次发布与其信息有关的公开公告。我们的主要结果表明,当代理商的私人信息是对事件结果的独立条件时,只要代理人对结果有类似的信念,他们的信息就会汇总。也就是说,没有错误的共识。 我们的主要结果基于自然信息理论框架有一个简短的证明。该框架的关键要素是``交互信息''的符号与人们信息价值的超级/亚addive属性之间的等效性。这提供了一种直观的解释和对交互信息的有趣应用,该信息衡量了三个随机变量共享的信息量。 我们通过依靠其中的另外两个结果来说明这些信息理论框架的力量:1)代理在宣布(摘要)以圆形罗宾方式宣布信念时很快同意[Aaronson 2005]; 2)[Chen等人2010]的结果是预测市场代理应发布信息以最大化其付款。我们还通过证明揭示信息的预期奖励是所揭示的信息的有条件相互信息,从而解释了预测市场的信息理论框架和上述结果。

We study a setting where Bayesian agents with a common prior have private information related to an event's outcome and sequentially make public announcements relating to their information. Our main result shows that when agents' private information is independent conditioning on the event's outcome whenever agents have similar beliefs about the outcome, their information is aggregated. That is, there is no false consensus. Our main result has a short proof based on a natural information theoretic framework. A key ingredient of the framework is the equivalence between the sign of the ``interaction information'' and a super/sub-additive property of the value of people's information. This provides an intuitive interpretation and an interesting application of the interaction information, which measures the amount of information shared by three random variables. We illustrate the power of this information theoretic framework by reproving two additional results within it: 1) that agents quickly agree when announcing (summaries of) beliefs in round robin fashion [Aaronson 2005]; and 2) results from [Chen et al 2010] on when prediction market agents should release information to maximize their payment. We also interpret the information theoretic framework and the above results in prediction markets by proving that the expected reward of revealing information is the conditional mutual information of the information revealed.

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