Max Planck Institute for Human Development Indiana University, Bloomington University of Basel Ohio University, Athens.
Cogn Sci. 2009 Jul;33(5):911-39. doi: 10.1111/j.1551-6709.2009.01034.x. Epub 2009 Apr 17.
People often face preferential decisions under risk. To further our understanding of the cognitive processes underlying these preferential choices, two prominent cognitive models, decision field theory (DFT; Busemeyer & Townsend, 1993) and the proportional difference model (PD; González-Vallejo, 2002), were rigorously tested against each other. In two consecutive experiments, the participants repeatedly had to choose between monetary gambles. The first experiment provided the reference to estimate the models' free parameters. From these estimations, new gamble pairs were generated for the second experiment such that the two models made maximally divergent predictions. In the first experiment, both models explained the data equally well. However, in the second generalization experiment, the participants' choices were much closer to the predictions of DFT. The results indicate that the stochastic process assumed by DFT, in which evidence in favor of or against each option accumulates over time, described people's choice behavior better than the trade-offs between proportional differences assumed by PD.
人们在面对风险时常常需要做出优先决策。为了更深入地了解这些优先选择背后的认知过程，我们严格地对比了两个著名的认知模型，决策域理论（DFT；Busemeyer & Townsend, 1993）和比例差异模型（PD；González-Vallejo, 2002）。在两个连续的实验中，参与者需要反复在金钱赌博中做出选择。第一个实验为估计模型的自由参数提供了参考。根据这些估计，为第二个实验生成了新的赌博组合，使得两个模型做出了最大的分歧预测。在第一个实验中，两个模型都同样能很好地解释数据。然而，在第二个推广实验中，参与者的选择更接近 DFT 的预测。结果表明，DFT 所假设的随机过程，即每种选择的赞成或反对证据随时间积累，比 PD 所假设的比例差异之间的权衡更好地描述了人们的选择行为。
