A Quantum Theoretical Explanation for Probability Judgment Errors
A Quantum Theoretical Explanation for Probability Judgment Errors
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DOI：
10.1037/a0022542
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发表时间：
2011-04-01
影响因子：
5.4
通讯作者：
Trueblood, Jennifer S.
中科院分区：
文献类型：
--
作者：
Busemeyer, Jerome R.;Pothos, Emmanuel M.;Trueblood, Jennifer S.
引入量子概率模型，用于解释人类概率判断错误，包括合取和析取谬误、平均效应、解包效应和推理顺序效应。一方面，量子理论与其他认知的分类和记忆模型相似，它依赖于由特征定义的向量空间和向量之间的相似性来确定概率判断。另一方面，量子概率论是贝叶斯概率论的推广，因为它基于一组（冯·诺伊曼）公理，这些公理放松了一些经典（柯尔莫哥罗夫）公理。量子模型与其他对这些判断错误的竞争性解释进行了比较和对比，包括概率判断的锚定和调整模型。在量子模型中，提出了一个新的认知基本概念：问题的相容性与不相容性及其对判断顺序的影响。我们的结论是，量子信息处理原理为理解人类的判断和推理提供了一种可行的、有前途的新方法。
A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and disjunction fallacies, averaging effects, unpacking effects, and order effects on inference. On the one hand, quantum theory is similar to other categorization and memory models of cognition in that it relies on vector spaces defined by features and similarities between vectors to determine probability judgments. On the other hand, quantum probability theory is a generalization of Bayesian probability theory because it is based on a set of (von Neumann) axioms that relax some of the classic (Kolmogorov) axioms. The quantum model is compared and contrasted with other competing explanations for these judgment errors, including the anchoring and adjustment model for probability judgments. In the quantum model, a new fundamental concept in cognition is advanced the compatibility versus incompatibility of questions and the effect this can have on the sequential order of judgments. We conclude that quantum information-processing principles provide a viable and promising new way to understand human judgment and reasoning.