Opponent Uses of Simplicity and Complexity in Causal Explanation
Opponent Uses of Simplicity and Complexity in Causal Explanation
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在因果解释中对简单性和复杂性的使用
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
F. Keil
中科院分区：
文献类型：
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作者：
S. Johnson;J. J. Valenti;F. Keil
人们通常更喜欢更简单的解释，因为它们有更高的先验概率。然而，简单的解释并不总是规范上的上级，因为它们往往不适合数据以及复杂的解释。人们如何在先验概率（偏好简单性）和拟合优度（偏好复杂性）之间进行权衡？在这里，我们认为，人们使用对手的竞争力依赖于简单性作为线索的先验概率，但复杂性作为线索的拟合优度（研究1）。我们还研究了导致一个或另一个启发式在给定的上下文中占主导地位的因素。研究2发现，人们在确定性而不是随机性背景下有更强的简单性偏好，而研究3发现，人们对物理因果系统而不是社会因果系统有更强的简单性偏好。总之，我们认为，这些线索和上下文主持人作为强大的约束，有助于指定，否则定义不清的假设比较问题。
People often prefer simpler explanations because they have higher prior probability. However, simpler explanations are not always normatively superior because they often do not fit the data as well as complex explanations. How do people negotiate this trade-off between prior probability (favoring simplicity) and goodness-of-fit (favoring complexity)? Here, we argue that people use opponent heuristics—relying on simplicity as a cue to prior probability but complexity as a cue to goodness-of-fit (Study 1). We also examine factors that lead one or the other heuristic to predominate in a given context. Study 2 finds that people have a stronger simplicity preference in deterministic rather than stochastic contexts, while Study 3 finds that people have a stronger simplicity preference for physical rather than social causal systems. Together, we argue that these cues and contextual moderators act as powerful constraints that help to specify otherwise illdefined hypothesis comparison problems.