情感预测作为一种适应性学习过程
Keisuke Takano1, Thomas Ehring2
1Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST).
Emotion (Washington, D.C.)
|October 12, 2023
概括
人类情感预测,或预测未来的情绪,不如统计模型准确,特别是在较长的时间范围内. 这表明人类可能有独特的预测错误,因为他们把当前的感受投射到未来的预测上.
科学领域:
- 认知心理学 认知心理学
- 情感科学是一种情感科学.
- 计算神经科学是一种神经科学.
背景情况:
- 人类情感预测被理论化为由预测错误驱动的适应性学习过程.
- 虽然卡尔曼波器可以模拟这个过程,但人类的预测往往是低于最佳的和有偏见的.
研究的目的:
- 将人类情感预测的准确性与卡尔曼波器生成的统计预测进行比较.
- 探索人类和统计情感预测过程之间的差异.
主要方法:
- 来自普通人群的参与者 (N=240) 进行了反复预测他们的情绪.
- 预测对未来的时间点进行了预测,从1分钟到2-3小时.
- 在三项研究中收集了日常生活和实验环境中的数据.
主要成果:
- 人类预测显示的绝对误差比卡尔曼波器预测更大,对于一个小时的预测 (dz = 0.42,0.30).
- 在分钟预测中,没有发现绝对误差的显著差异 (dz = 0.17).
- 参与者表现出一种一致的偏见,即将当前的情感状态投射到未来的预测中.
结论:
- 人类情感预测的准确性低于较长时间的统计模型.
- 预测当前影响的趋势可能是人类特定预测错误的基础.
- 研究结果突出了人类情绪预测中的最佳预测误差驱动学习的潜在偏差.
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