在结果不确定性下研究决策的新方法-避免任务
Ziwei Cheng1, Nadja R Ging-Jehli2, Maisy Tarlow2
1Department of Psychology, University of California Berkeley, Berkeley, CA, United States.
人们在不确定性下做决定时平衡奖励和风险. 计算模型表明,决策速度反映了积极结果与负面结果的影响.
科学领域:
- 认知神经科学 认知神经科学
- 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:
- 适应性行为需要整合概率结果和平衡方法避免倾向.
- 结果不确定性对方法避免决策动态的影响仍然不完全理解.
研究的目的:
- 调查积极和负面结果的不确定性如何影响方法-避免决策.
- 开发和验证一个新的任务和计算模型来研究这些动态.
主要方法:
- 一种概率方法避免任务 (PAAT) 的开发.
- 使用顺序采样模型进行行为特征.
- 参与者 (N=34) 在具有可变奖励概率和厌恶结果概率的选项之间做出选择.
主要成果:
- 参与者优先选择,最大限度地提高奖励可能性,最大限度地降低不利结果的可能性.
- 奖励与厌恶的权重根据结果对齐而有所不同 (一致与不一致的试验).
- 计算模型表明,信息积累率反映了奖励和厌恶的相对影响.
结论:
- 序列采样模型可靠地捕获行为数据,验证了它们的实用性.
- 这些发现增强了对如何激励冲突,结果类型和不确定性塑造方法避免决策的理解.
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