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Design Improved Parimutuel-type Information Aggregation Mechanisms: Inaccuracies and the Long-Shot Bias as Disequilibrium Phenomena

机译:设计改进的Parimutuel型信息聚合机制:误差和长期不平衡现象作为不平衡现象

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摘要

Information Aggregation Mechanisms (IAMs) based on parimutuel-type betting systems can aggregate information from complex environments. However, the performance of previously studied systems leaves something to be desired due to possible bluffing, strategic timing of decisions and a so called long shot bias. This paper demonstrates that two modifications of parimutuel systems improve information aggregation performance by removing disinformation due to strategic behavior and by removing misleading disequilibrium behavior. The experiments also demonstrate that the so called long shot bias results from disequilibrium behavior as opposed to having roots in the psychology of the individuals.
机译:基于稀疏类型下注系统的信息汇总机制(IAM)可以汇总来自复杂环境的信息。但是,由于可能的虚张声势,决策的战略时机以及所谓的长期偏见,先前研究过的系统的性能仍有待改进。本文证明,对parimutuel系统的两种修改可通过消除由于战略行为引起的虚假信息和消除误导性的不平衡行为而提高信息聚合性能。实验还表明,所谓的远距离偏见是由不平衡行为引起的,而不是植根于个体的心理。

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