A Geometric Method to Construct Minimal Peer Prediction Mechanisms

A Geometric Method to Construct Minimal Peer Prediction Mechanisms
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构建最小同行预测机制的几何方法

DOI：
10.1609/aaai.v30i1.10050
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发表时间：
2016
期刊：
ArXiv
影响因子：
--
通讯作者：
Jens Witkowski
Jens Witkowski
中科院分区：
--
文献类型：
--
作者：
Rafael M. Frongillo;Jens Witkowski

文献摘要

被引文献

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最小对等预测机制真实地引出私有信息（例如，意见或经验），而不需要最终揭示地面真相。在本文中，我们使用几何的角度来证明，最小的同行预测机制是等价的权力图，一种加权Voronoi图。使用这种表征和计算几何的结果，我们表明，在文献中的许多机制是唯一的仿射变换，并介绍了一种通用的方法来构建新的真实的机制。
Minimal peer prediction mechanisms truthfully elicit private information (e.g., opinions or experiences) from rational agents without the requirement that ground truth is eventually revealed. In this paper, we use a geometric perspective to prove that minimal peer prediction mechanisms are equivalent to power diagrams, a type of weighted Voronoi diagram. Using this characterization and results from computational geometry, we show that many of the mechanisms in the literature are unique up to affine transformations, and introduce a general method to construct new truthful mechanisms.