贝叶斯在数量估计中的社会和内生不确定性的最佳整合
Tutku Öztel1, Fuat Balcı1,2
1Psychology Department, Koç University.
Cognitive science
|April 24, 2024
概括
当社会信息比他们自己的信息更可靠时,人类符合群体的估计,这表明贝叶斯最佳社会一致性. 这表明一个隐含的元认知过程影响了在模两可的情况下的决策.
科学领域:
- 认知心理学 认知心理学
- 社会神经科学 社会神经科学
- 决策科学科学 决策科学
背景情况:
- 社会影响对人类决策产生重大影响,特别是在含糊不清的感知信息方面.
- 贝叶斯最优理论建议基于它们相对可靠性的内生和社会信息的整合.
研究的目的:
- 调查人类是否在人数估计过程中以贝叶斯最佳方式整合社会和内源信息统计 (平均值,方差).
- 确定在决策过程中社会一致性发生的条件.
主要方法:
- 参与者估计了人数,提供了个人 (内生) 和团体 (社会) 信息.
- 两个信息源的统计属性 (平均值,方差) 被操纵和分析.
- 分析了行为数据,以评估社会和内生信息的整合.
主要成果:
- 人类参与者在小组信息比他们自己的内部不确定性更可靠时,选择性地调整了他们对小组平均值的初步估计.
- 这种调整模式与贝叶斯最佳社会一致性预测一致.
- 有证据表明,这种适应性社会学习的基础是隐含的元认知过程.
结论:
- 人类通过根据其可靠性相对于内源信息来权衡社会信息来表现贝叶斯最佳社会一致性.
- 这些发现突显了元认知在调节社会对感知和决策的影响中的作用.
- 这项研究提供了对人类社会学习和信息整合机制的见解.
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