概率判断“错误”的量子概率解释
Quantum Probability Explanations for Probability Judgment 'Errors'
摘要：
引入了一个量子概率模型来解释人类的概率判断错误，包括合取、析取、逆和条件谬误，以及拆包效应和分割效应。量子概率论是一种基于一组（冯诺依曼）公理的一般和连贯的理论，这些公理放松了经典（柯尔莫哥洛夫）概率论的一些约束。量子模型进行了比较，并与其他竞争的解释，这些判断错误，包括代表性启发式，平均模型，和记忆检索模型的概率判断。量子模型还提供了扩展贝叶斯、模糊集和模糊迹理论的方法。我们的结论是，量子信息处理原理提供了一个可行的和有前途的新方法来理解人类的判断和推理。
英文摘要：
A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction, disjunction, inverse, and conditional fallacies, as well as unpacking effects and partitioning effects. Quantum probability theory is a general and coherent theory based on a set of (von Neumann) axioms which relax some of the constraints underlying classic (Kolmogorov) probability theory. The quantum model is compared and contrasted with other competing explanations for these judgment errors including the representativeness heuristic, the averaging model, and a memory retrieval model for probability judgments. The quantum model also provides ways to extend Bayesian, fuzzy set, and fuzzy trace theories. We conclude that quantum information processing principles provide a viable and promising new way to understand human judgment and reasoning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
