构建世界的压缩因果模型
David Kinney1, Tania Lombrozo2
1Department of Philosophy and Program in Philosophy-Neuroscience Psychology, Washington University in St. Louis, United States.
Cognitive psychology
|October 20, 2024
概括
代理人通过平衡信息压缩和对决策的有用性来创建简化的因果模型. 他们更喜欢更简单的模型,当丢失的信息对决策不至关重要时,多项研究证实了这一点.
科学领域:
- 认知科学 认知科学
- 科学哲学的哲学科学哲学
- 人工智能的人工智能
背景情况:
- 因果系统可以以多种方式表示.
- 代理人必须选择因果表示的变量和细粒度.
研究的目的:
- 开发一种正式的理论,解释代理人如何选择因果表示.
- 调查因果模型中压缩和信息性之间的权衡.
主要方法:
- 利用贝叶斯网络,信息理论和决策理论.
- 开发了一个正式的模型,预测对因果表示的偏好.
- 进行了七项实证研究 (N=2546名参与者).
主要成果:
- 当信息损失最小时,代理者更喜欢压缩的因果模型.
- 如果丢失的数据影响决策,代理人就会牺牲压缩来获得信息.
- 经验发现与发展理论的预测保持一致.
结论:
- 因果表示受压缩-信息性权衡的支配.
- 这种权衡是由信息的决策理论价值调节的.
- 压缩的因果表示是人类认知和评估的核心.
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