title: A Simplified Model of Choice Behavior under Uncertainty.
abstract: The Iowa Gambling Task (IGT) has been standardized as a clinical assessment tool (Bechara, 2007). Nonetheless, numerous research groups have attempted to modify IGT models to optimize parameters for predicting the choice behavior of normal controls and patients. A decade ago, most researchers considered the expected utility (EU) model (Busemeyer and Stout, 2002) to be the optimal model for predicting choice behavior under uncertainty. However, in recent years, studies have demonstrated that models with the prospect utility (PU) function are more effective than the EU models in the IGT (Ahn et al., 2008). Nevertheless, after some preliminary tests based on our behavioral dataset and modeling, it was determined that the Ahn et al. (2008) PU model is not optimal due to some incompatible results. This study aims to modify the Ahn et al. (2008) PU model to a simplified model and used the IGT performance of 145 subjects as the benchmark data for comparison. In our simplified PU model, the best goodness-of-fit was found mostly as the value of α approached zero. More specifically, we retested the key parameters α, λ, and A in the PU model. Notably, the influence of the parameters α, λ, and A has a hierarchical power structure in terms of manipulating the goodness-of-fit in the PU model. Additionally, we found that the parameters λ and A may be ineffective when the parameter α is close to zero in the PU model. The present simplified model demonstrated that decision makers mostly adopted the strategy of gain-stay loss-shift rather than foreseeing the long-term outcome. However, there are other behavioral variables that are not well revealed under these dynamic-uncertainty situations. Therefore, the optimal behavioral models may not have been found yet. In short, the best model for predicting choice behavior under dynamic-uncertainty situations should be further evaluated.
authors: Department of Psychology, Soochow UniversityTaipei, Taiwan; Department of Psychology, Kaohsiung Medical UniversityKaohsiung, Taiwan; Research Center for Nonlinear Analysis and Optimization, Kaohsiung Medical UniversityKaohsiung, Taiwan; Biomedical Engineering Research and Development Center, China Medical University HospitalTaichung, Taiwan.
authors: Ching-Hung
authors: CH
authors: Lin
authors: Department of Psychology, Soochow University Taipei, Taiwan.
authors: Yu-Kai
authors: YK
authors: Lin
authors: Department of Psychology, Soochow University Taipei, Taiwan.
authors: Tzu-Jiun
authors: TJ
authors: Song
authors: Graduate Institute of Neural and Cognitive Sciences, China Medical University Taichung, Taiwan.
authors: Jong-Tsun
authors: JT
authors: Huang
authors: Department of Psychology, Soochow University Taipei, Taiwan.
authors: Yao-Chu
authors: YC
authors: Chiu
keywords: Iowa Gambling Task; delta learning rule; dynamic-uncertainty situations; expected utility model; gain-loss frequency; loss aversion; prominent deck B phenomenon; prospect utility model