From Monetary to Non-Monetary Mechanism Design via Artificial Currencies

Artur Gorokh, Siddhartha Banerjee, Krishnamurthy Iyer
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引用次数: 38

Abstract

Non-monetary mechanisms for repeated resource allocation are gaining widespread use in many real-world settings. Our aim in this work is to study the allocative efficiency and incentive properties of simple repeated mechanisms based on artificial currencies. Within this framework, we make three main contributions: We provide a general black-box technique to convert any static monetary mechanism to a dynamic mechanism with artificial currency, that simultaneously guarantees vanishing loss in efficiency, and vanishing gains from non-truthful bidding over time. On a computational front, we show how such a mechanism can be implemented using only sample-access to the agents' type distributions, and requires roughly twice the amount of computation as needed to run the monetary mechanism alone. For settings with two agents, we show that a particular artificial currency mechanism also results in a vanishing price of anarchy. This provides additional justification for the use of artificial currency mechanisms in practice. Moreover, we show how to leverage this result to demonstrate the existence of a Bayesian incentive-compatible mechanism with vanishing efficiency loss in this setting. Our work takes a significant step towards bridging the gap between monetary and non-monetary mechanisms, and also points to several open problems.
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从货币机制设计到非货币机制设计
用于重复资源配置的非货币机制在许多现实环境中得到广泛应用。本研究的目的是研究基于人工货币的简单重复机制的配置效率和激励特性。在这个框架内,我们做出了三个主要贡献:我们提供了一种通用的黑盒技术,将任何静态货币机制转换为具有人工货币的动态机制,同时保证了效率损失的消失,以及随着时间的推移,不真实竞标的收益消失。在计算方面,我们展示了如何仅使用对代理类型分布的样本访问来实现这样的机制,并且需要的计算量大约是单独运行货币机制所需的两倍。对于具有两个代理的设置,我们证明了特定的人工货币机制也会导致无政府状态的价格消失。这为在实践中使用人工货币机制提供了额外的理由。此外,我们展示了如何利用这一结果来证明贝叶斯激励相容机制的存在,在这种情况下,效率损失消失。我们的工作在弥合货币和非货币机制之间的差距方面迈出了重要的一步,同时也指出了几个悬而未决的问题。
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