ISSN 0439-755X
CN 11-1911/B

心理学报 ›› 2023, Vol. 55 ›› Issue (11): 1793-1805.doi: 10.3724/SP.J.1041.2023.01793

• 研究报告 • 上一篇    下一篇


胡馨允, 沈悦, 戴俊毅()   

  1. 浙江大学心理与行为科学系, 杭州 310058
  • 收稿日期:2023-02-02 发布日期:2023-08-30 出版日期:2023-11-25
  • 通讯作者: 戴俊毅, E-mail:
  • 基金资助:

Strategy switching in a sequence of decisions: Evidence from the Iowa Gambling Task

HU Xinyun, SHEN Yue, DAI Junyi()   

  1. Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
  • Received:2023-02-02 Online:2023-08-30 Published:2023-11-25


已有大量研究使用系列决策任务探讨了各类决策的决策策略。通过假定个体采用单一策略完成所有任务试次, 并比较对应的计算认知模型拟合实证数据的能力, 这些研究发现各种决策任务都涉及多种可能的决策策略。但是, 此类研究的一个共同缺陷在于忽视了个体在任务过程中转换决策策略的可能性。通过开发允许在强化学习策略和启发式策略间转换的针对爱荷华赌博任务的计算认知模型, 并将此类模型同单一策略模型进行对比, 研究1提供了个体在该系列决策任务中会改变决策策略的明确证据。研究2则发现, 随着试次数的增加, 发生策略转换的可能性也会上升。这些结果表明, 为了正确认识各种决策任务的决策策略, 需要充分考虑在系列决策任务过程中发生策略转换的可能性, 尤其是试次较多的系列任务。未来研究可以探讨策略转换的多种可能形式, 以及导致策略转换的任务和个体因素, 以便进一步深化对于系列决策任务的心理机制的认识。

关键词: 系列决策任务, 爱荷华赌博任务, 策略转换, 计算认知建模, 强化学习和启发式策略


Much research has been devoted to studying decision strategies in various tasks. Such research usually involved a sequence of decision trials under the same task structure to provide sufficient information for inferring the underlying decision strategies. By assuming each individual adopted a single decision strategy across all decision trials and comparing corresponding computational cognitive models in terms of their performances in fitting empirical data, such studies have revealed multiple possible decision strategies for many major decision tasks. One common drawback of such research, however, was overlooking the possibility that individuals switched their strategies along the sequence of decisions. This might lead to inappropriate conclusions regarding the decision strategies underlying specific decision tasks or misleading inferences of potential cognitive and affective differences between normal and different clinical populations based on parameter estimates from models assuming single strategies.
To address this critical issue, two studies were conducted to examine the possibility of strategy switching in the Iowa Gambling Task (IGT), an experience-based decision task with a sequence of trials aimed at mimicking real-world decisions under uncertainty. By developing a computational cognitive model that allowed for switches between reinforcement learning strategies and heuristic strategies and comparing its performance with those of single-strategy models, Study 1 showed that data from about half of the 617 healthy participants in 10 previous studies were better fitted by the strategy-switching model than three single-strategy models that performed well in previous research, that is, the WSLS, PVL2, and VPP models as exemplar models assuming heuristic, reinforcement learning, and mixed strategies, respectively. This result provided clear support for the possibility of strategy switching in the IGT.
Since strategy switching might occur with accumulating experience or fatigue and an increasing number of trials is likely to facilitate such changes, 321 participants were recruited in Study 2 to further examine whether a larger number of trials would contribute to more strategy switching in the IGT. Specifically, 160 participants performed a 100-trial IGT, whereas the other 161 participants performed a 200-trial IGT under otherwise the same task structure. It was found that data from a larger proportion of individual participants were best fitted by the strategy-switching model when the IGT involved 200 trials rather than standard 100 trials. This result provided further evidence for strategy switching in the task.
Overall, the current results suggest that strategy switching is likely to occur in a sequence of decisions under the same task structure. Consequently, in order to obtain proper understanding of the decision strategies for various decision tasks, it is necessary to consider seriously the possibility of strategy switching, especially for a long sequence of decisions. For a more refined understanding of psychological mechanisms underlying sequences of decisions, future research might further investigate various forms of strategy switching such as gradual instead of abrupt switches and task and individual factors that trigger such switches.

Key words: decision task with a sequence of trials, The Iowa Gambling Task, strategy switching, computational cognitive modeling, reinforcement learning and heuristic strategies