Cognitive Psychology, School of Humanities and Social Sciences, Jacobs University Bremen, Germany.
Mathematics, Modeling, and Computing Center, School of Engineering and Science, Jacobs University Bremen, Germany.
Front Hum Neurosci. 2014 Sep 9;8:697. doi: 10.3389/fnhum.2014.00697. eCollection 2014.
A sequential sampling model for multiattribute binary choice options, called multiattribute attention switching (MAAS) model, assumes a separate sampling process for each attribute. During the deliberation process attention switches from one attribute consideration to the next. The order in which attributes are considered as well for how long each attribute is considered-the attention time-influences the predicted choice probabilities and choice response times. Several probability distributions for the attention time with different variances are investigated. Depending on the time and order schedule the model predicts a rich choice probability/choice response time pattern including preference reversals and fast errors. Furthermore, the difference between finite and infinite decision horizons for the attribute considered last is investigated. For the former case the model predicts a probability p 0 > 0 of not deciding within the available time. The underlying stochastic process for each attribute is an Ornstein-Uhlenbeck process approximated by a discrete birth-death process. All predictions are also true for the widely applied Wiener process.
一种用于多属性二项选择选项的顺序抽样模型，称为多属性注意切换（MAAS）模型，假设每个属性都有一个单独的抽样过程。在审议过程中，注意力从一个属性的考虑切换到下一个属性的考虑。属性被考虑的顺序以及每个属性被考虑的时间——注意时间——会影响预测的选择概率和选择反应时间。研究了几种具有不同方差的注意力时间的概率分布。根据时间和顺序安排，该模型预测了一种丰富的选择概率/选择反应时间模式，包括偏好反转和快速错误。此外，还研究了最后考虑的属性的有限和无限决策范围之间的差异。在前一种情况下，模型预测在可用时间内不做出决定的概率 p0>0。每个属性的基础随机过程是一个 Ornstein-Uhlenbeck 过程，由离散的生死过程近似。所有预测对于广泛应用的 Wiener 过程也是正确的。
