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The Effect of Evidential Impact on Perceptual Probabilistic Judgments
Cognitive Science ( IF 2.3 ) Pub Date : 2021-01-04 , DOI: 10.1111/cogs.12919
Marta Mangiarulo 1 , Stefania Pighin 1 , Luca Polonio 2 , Katya Tentori 1
Affiliation  

In a series of three behavioral experiments, we found a systematic distortion of probability judgments concerning elementary visual stimuli. Participants were briefly shown a set of figures that had two features (e.g., a geometric shape and a color) with two possible values each (e.g., triangle or circle and black or white). A figure was then drawn, and participants were informed about the value of one of its features (e.g., that the figure was a “circle”) and had to predict the value of the other feature (e.g., whether the figure was “black” or “white”). We repeated this procedure for various sets of figures and, by varying the statistical association between features in the sets, we manipulated the probability of a feature given the evidence of another (e.g., the posterior probability of hypothesis “black” given the evidence “circle”) as well as the support provided by a feature to another (e.g., the impact, or confirmation, of evidence “circle” on the hypothesis “black”). Results indicated that participants’ judgments were deeply affected by impact, although they only should have depended on the probability distributions over the features, and that the dissociation between evidential impact and posterior probability increased the number of errors. The implications of these findings for lower and higher level cognitive models are discussed.

中文翻译:

证据影响对感知概率判断的影响

在一系列三个行为实验中,我们发现关于基本视觉刺激的概率判断存在系统性失真。向参与者简要展示了一组图形,这些图形具有两个特征(例如,几何形状和颜色),每个特征具有两个可能的值(例如,三角形或圆形以及黑色或白色)。然后绘制一个图形,参与者被告知其中一个特征的值(例如,该图形是一个“圆圈”),并且必须预测另一个特征的值(例如,该图形是否为“黑色”)或“白色”)。我们对不同的图形集重复了这个过程,并通过改变集合中特征之间的统计关联,在给定另一个特征的证据的情况下操纵了一个特征的概率(例如,假设“黑色”的后验概率给定证据“圆圈”)以及特征提供给另一个特征的支持(例如,证据“圆圈”对假设“黑色”的影响或确认)。结果表明,参与者的判断深受影响,尽管他们应该只依赖于特征的概率分布,而且证据影响和后验概率之间的分离增加了错误的数量。讨论了这些发现对低级和高级认知模型的影响。尽管它们应该只取决于特征的概率分布,而且证据影响和后验概率之间的分离增加了错误的数量。讨论了这些发现对低级和高级认知模型的影响。尽管它们应该只取决于特征的概率分布,而且证据影响和后验概率之间的分离增加了错误的数量。讨论了这些发现对低级和高级认知模型的影响。
更新日期:2021-01-08
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