Research has shown that aggregation of independent expert judgments significantly improves the quality of forecasts as compared to individual expert forecasts. This “wisdom of crowds” (WOC) has sparked substantial interest. However, previous studies on strengths and weaknesses of aggregation algorithms have been restricted by limited empirical data and analytical complexity. Based on a comprehensive analysis of existing knowledge on WOC and aggregation algorithms, this paper describes the design and implementation of a static stochastic simulation model to emulate WOC scenarios with a wide range of parameters. The model has been thoroughly evaluated: the assumptions are validated against propositions derived from literature, and the model has a computational representation. The applicability of the model is demonstrated by investigating aggregation algorithm behavior on a detailed level, by assessing aggregation algorithm performance, and by exploring previously undiscovered suppositions on WOC. The simulation model helps expand the understanding of WOC, where previous research was restricted. Additionally, it gives directions for developing aggregation algorithms and contributes to a general understanding of the WOC phenomenon.

中文翻译：

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一种基于模拟的方法来理解聚集专家判断中的人群现象的智慧

研究表明，与个人专家预测相比，独立专家判断的汇总显着提高了预测质量。这种“群体智慧”（W​​OC）引起了极大的兴趣。然而，先前关于聚合算法优缺点的研究受到有限的经验数据和分析复杂性的限制。本文基于对 WOC 和聚合算法现有知识的综合分析，描述了静态随机仿真模型的设计和实现，以模拟具有广泛参数的 WOC 场景。该模型已经过全面评估：根据文献中的命题验证了假设，并且该模型具有计算表示。该模型的适用性通过详细研究聚合算法行为、评估聚合算法性能以及探索先前未发现的关于 WOC 的假设来证明。模拟模型有助于扩展对 WOC 的理解，因为先前的研究受到限制。此外，它还为开发聚合算法提供了方向，并有助于对 WOC 现象的一般理解。