一个理性过程模型,用连续变量进行因果推理.
1Psychology Department, New York University, 6 Washington Place, NY, NY 10012, United States.
Cognition
|June 28, 2025
概括
人们会有系统地犯因果推理错误,即使是连续变量. 一种突变采样模型解释了这些错误是由于认知资源的限制而产生的,用二进制变量扩展了以前的发现.
科学领域:
- 认知科学 认知科学
- 心理学 心理学 心理学
- 因果推理因果推理
背景情况:
- 人类是有效的因果推理者,但容易产生系统错误.
- 突变采样模型通过假设由认知资源限制的理性推断来解释这一点.
- 之前的测试集中在二进制变量和生成因果关系上.
研究的目的:
- 用连续变量实证测试突变采样模型.
- 在具有混合生成和抑制关系的共同原因网络中调查因果推理.
- 确定因果推理中的人类错误是否延伸到连续变量.
主要方法:
- 用连续变量进行因果推理的实证测试.
- 使用一个共同的原因网络结构.
- 使用生成和抑制因果关系的混合.
- 应用突变采样模型的新版本,用于连续变量.
主要成果:
- 人们在连续变量和二进制变量的因果推理中犯下类似的定性错误.
- 突变采样器的新版本准确地解释了这些错误.
- 突变采样器的采样过程对所有因果推断产生定量影响,而不仅仅是错误的推断.
结论:
- 突变采样模型为跨变量类型的人类因果推理错误提供了强有力的解释.
- 认知资源的局限性显著影响连续变量的因果推理.
- 该模型的定量效应突出显示了采样过程对推断的普遍影响.
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