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首页> 外文期刊>Cognitive Science >Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?
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Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?

机译：日常认知中的最佳预测：个人还是人群的智慧？

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Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were optimal, employing Bayesian inference based on veridical prior distributions. Although the predictions conformed strikingly to statistics of the world, they reflect averages over many individuals. On the conjecture that the accuracy of the group response is chiefly a consequence of aggregating across individuals, we constructed simple, heuristic approximations to the Bayesian model premised on the hypothesis that individuals have access merely to a sample of k instances drawn from the relevant distribution. The accuracy of the group response reported by Griffiths and Tenenbaum could be accounted for by supposing that individuals each utilize only two instances. Moreover, the variability of the group data is more consistent with this small-sample hypothesis than with the hypothesis that people utilize veridical or nearly veridical representations of the underlying prior distributions. Our analyses lead to a qualitatively different view of how individuals reason from past experience than the view espoused by Griffiths and Tenenbaum.
机译：Griffiths和Tenenbaum（2006）要求个人对日常事件的持续时间或程度（例如蛋糕烘烤时间）做出预测，并报告说预测是最佳的，它采用基于先验先验分布的贝叶斯推断。尽管这些预测与世界统计数据惊人地吻合，但它们反映了许多个人的平均值。推测群体响应的准确性主要是个体之间聚合的结果，我们以贝叶斯模型为基础构造简单，启发式近似，其前提是个体只能访问从相关分布中提取的k个实例的样本。格里菲斯（Griffiths）和特南鲍姆（Tenenbaum）报告的小组回答的准确性可以通过假设每个人仅利用两个实例来解释。此外，组数据的可变性与这种小样本假设相比，与人们利用基础先验分布的垂直或近似垂直表示的假设更为一致。与格里菲斯和特南鲍姆所拥护的观点相比，我们的分析得出了关于个人如何根据过去经验进行推理的质性观点。

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