建模决策偏见的模型
Ettore Cerracchio1, Steven Miletić1, Birte U Forstmann1
1Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.
Frontiers in computational neuroscience
|November 6, 2023
概括
数学认知模型,特别是证据积累模型,比统计模型更全面地了解决策偏见. 这些模型包括响应时间,为注意力和期望偏差提供了更深入的见解.
科学领域:
- 认知心理学 认知心理学
- 计算神经科学是一种计算神经科学.
- 决策科学科学 决策科学
背景情况:
- 决策偏见是人类行为的组成部分.
- 统计模型提供了描述性的见解,但缺乏预测能力,可以被模两可地解释.
- 数学认知模型为预测和模拟决策过程提供了正式假设.
研究的目的:
- 为了比较信号检测理论和证据积累模型在捕获决策偏见方面的有效性.
- 研究注意力和期望对认知过程的影响.
- 质疑现有的关于注意力和先前概率对决策参数的影响的发现.
主要方法:
- 用信号检测理论和证据积累模型进行研究的比较分析.
- 使用证据积累模型对注意力和期望偏差的最新研究进行审查.
- 检查挑战既定参数影响的新发现.
主要成果:
- 证据积累模型通过结合响应时间数据,提供了更完整的决策偏见.
- 注意力不仅影响证据积累的速度,还影响非决策时间.
- 预先概率不仅影响起点,还影响证据积累的漂移速度.
结论:
- 证据积累模型在理解决策偏见方面优于统计模型.
- 新发现需要对注意力和先前概率如何调节认知决策参数进行修订理解.
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