Output Agreement Mechanisms and Common Knowledge
Output Agreement Mechanisms and Common Knowledge
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输出协议机制和常识
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Yiling Chen
中科院分区：
文献类型：
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作者：
Bo Waggoner;Yiling Chen
人类计算的最新出现 - 采用非专家来解决问题 - 在无法验证响应时，启发了机理设计中的理论工作，以引发信息。我们从理论的角度研究一种流行的实用方法，即输出协议。在输出协议中，给出了两个代理相同的输入，并要求产生一些输出。根据他们的回应如何同意。尽管简单，输出协议提出了新的概念问题。主要知识的基本重要性是：我们表明，输出一致性机制而不是真实，而是引起参与者的常识。我们表明，除非对信息结构受到限制，否则常见知识本质上是可以在没有验证的任何机制中获得的最好的知识。这涉及概括真实性，以包括响应查询，而不是简单地报告私人信号，以及共同的知识平衡概念。产出协议提出的最后一个重要问题是局部平衡和均衡的球员计算。我们表明，为了引发随机变量的平均值，天然玩家推理过程会收敛到共同的知识平衡。但是其他类型的查询可能不会发生这种收敛。
The recent advent of human computation -- employing non-experts to solve problems -- has inspired theoretical work in mechanism design for eliciting information when responses cannot be verified. We study a popular practical method, output agreement, from a theoretical perspective. In output agreement, two agents are given the same inputs and asked to produce some output; they are scored based on how closely their responses agree. Although simple, output agreement raises new conceptual questions. Primary is the fundamental importance of common knowledge: We show that, rather than being truthful, output agreement mechanisms elicit common knowledge from participants. We show that common knowledge is essentially the best that can be hoped for in any mechanism without verification unless there are restrictions on the information structure. This involves generalizing truthfulness to include responding to a query rather than simply reporting a private signal, along with a notion of common-knowledge equilibria. A final important issue raised by output agreement is focal equilibria and player computation of equilibria. We show that, for eliciting the mean of a random variable, a natural player inference process converges to the common-knowledge equilibrium; but this convergence may not occur for other types of queries.