积累证据对于产生时间间偏好并非必不可少:对匹配任务的动态认知模型进行比较
Xuhui Zhang1, Zhuoyi Fan1, Yue Shen1
1Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.
Cognitive psychology
|October 23, 2023
概括
一个匹配的范式提供了比选择任务更深入地了解时间间偏好. 随机实用性和歧视值 (RUDT) 框架,是一种基于属性的方法,最好地解释这些偏好而不需要证据积累.
科学领域:
- 认知心理学 认知心理学
- 决策科学 决策科学 决策科学
- 行为经济学是一种行为经济学.
背景情况:
- 时间间偏好研究主要使用选择范式.
- 匹配范式为理解时间间偏好和潜在的认知机制提供了一个潜在的更具信息性的方法.
- 现有模型通常假定证据积累,但其他框架需要调查.
研究的目的:
- 用匹配范式研究时间间偏好.
- 在证据积累和非证据积累框架内比较动态模型.
- 确定时间间决策的认知基础.
主要方法:
- 两项实证研究采用了匹配范式来评估时间间偏好.
- 模型是根据决策场理论 (证据积累) 和随机效用和歧视值 (RUDT) 框架 (非证据积累) 开发的.
- 参与者匹配了即时和延迟的刺激,任务在所需匹配参数 (数量或延迟) 中有所不同.
主要成果:
- 在匹配值和响应时间方面观察到一致的行为规律.
- 模型比较有利于RUDT框架和基于属性的时间间偏好视角.
- 最好的RUDT模型准确地预测了观察到的匹配值和响应时间,复制了关键的行为模式.
结论:
- 积累证据并不是产生时间间偏好的必要条件.
- RUDT框架与基于属性的方法相结合,为时间间偏好提供了强有力的解释.
- 未来的研究应该在其他优先决策环境中验证这一框架.
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