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arXiv 1202.3710cs.GTcs.AI
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严格适当的机制与合作的球员

Strictly Proper Mechanisms with Cooperating Players

Stanford University(斯坦福大学)

SangIn Chun, Ross D. Shachter

摘要:

预测市场提供了一种有效的手段来评估预测者的不确定数量。传统的和竞争性的严格适当的评分规则已被证明可以激励玩家提供真实的概率预测。然而,我们表明,当这些玩家可以合作时,这些机制反而会阻止他们报告他们真正相信的东西。当不同信念的参与者能够合作并形成联盟时,这些机制允许套利,并且有一份报告将永远支付联盟成员比他们真实预测更多的钱。如果联盟是由一个中间人创建的,比如一个门户网站,那么中间人就可以保证盈利。

英文摘要:

Prediction markets provide an efficient means to assess uncertain quantities from forecasters. Traditional and competitive strictly proper scoring rules have been shown to incentivize players to provide truthful probabilistic forecasts. However, we show that when those players can cooperate, these mechanisms can instead discourage them from reporting what they really believe. When players with different beliefs are able to cooperate and form a coalition, these mechanisms admit arbitrage and there is a report that will always pay coalition members more than their truthful forecasts. If the coalition were created by an intermediary, such as a web portal, the intermediary would be guaranteed a profit.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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