弥合主观概率和概率判断之间的差距:量子序列采样器
Jiaqi Huang1, Jerome R Busemeyer1, Zo Ebelt2
1Department of Cognitive Science, Indiana University.
Psychological review
|September 19, 2024
概括
本研究介绍了量子序列采样器,这是一个新的概率推理模型,它集成了贝叶斯和量子理论. 它解释了认知谬论,并揭示了人类决策中的概率令人惊的高估.
科学领域:
- 认知科学 认知科学
- 决策理论 决策理论
- 心理学 心理学 心理学
背景情况:
- 将贝叶斯理论与常见的概率推理谬误相协调是一个关键的挑战.
- 显而易见的谬误通常归因于贝叶斯概率估计中的采样错误或偏见.
- 量子概率规则为这些认知现象提供了另一种解释.
研究的目的:
- 开发一个统一的框架,将贝叶斯和量子影响纳入人类的概率推理.
- 解决超越当前贝叶斯和量子模型的经验发现.
- 为概率推理提出一种新的模型,该模型能够解释贝叶斯式和量子方面.
主要方法:
- 量子序列采样器模型的开发,将贝叶斯式和量子推理与序列采样相结合.
- 量子序列采样器与领先的贝叶斯采样器模型的比较.
- 进行一个新的实验,以生成一个大数据集用于概率推理分析.
主要成果:
- 量子序列采样器为概率推理提供了更准确的理论方法.
- 经验测试揭示了一个新的和系统的概率高估.
- 新模型为广泛的发现提供了更统一的解释.
结论:
- 量子序列采样器有效地整合了贝叶斯式和量子认知模型.
- 该模型提升了我们对人类概率推理和决策的理解.
- 进一步的研究是有必要的,以探索系统的概率高估的影响.
相关概念视频
Probability in Statistics
12.4K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
12.4K
Propagation of Uncertainty from Random Error
656
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
656
Probability Distributions
6.8K
The probability of a random variable x is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
6.8K
Probability Laws
40.7K
Overview
40.7K
Propagation of Uncertainty from Systematic Error
490
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
490
Probability Histograms
11.1K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
11.1K


