行动重复在取决于背景的决策中产生偏见的选择
Ben J Wagner1,2, H Benedikt Wolf3, Stefan J Kiebel3,4
1Chair of Cognitive Computational Neuroscience, Faculty of Psychology, TU Dresden, Germany. ben.jonathan.wagner@gmail.com.
人类的决策偏见可能源于重复的特定情境的行为. 一个结合奖励学习和行动重复的新模型有效地解释了这些偏见,优于其他计算模型.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 行为经济学是一种行为经济学.
背景情况:
- 决策偏见使人类行为看起来不理性.
- 取决于背景的选择受到过去经验的影响.
- 现有的计算模型往往需要大量的环境数据.
研究的目的:
- 测试决策偏见是否是由特定环境的行动重复驱动的.
- 开发和验证一个解释这些偏差的计算模型.
主要方法:
- 与351名参与者进行了9个基于价值的决策任务.
- 重新分析了6个先前的数据集,涉及350名参与者.
- 开发了一个分层的贝叶斯强化学习模型,包括奖励学习和动作重复.
主要成果:
- 更多的语境内行动重复与偏见的选择相关,包括更高的主观评估和更低的不确定性.
- 提出的模型成功地解释了稳定的环境中的偏见选择.
- 模型比较表明,与价值规范化和以目标为中心的账户相比,表现优越.
结论:
- 行动重复是决定偏见的关键驱动力.
- 结合奖励学习和行动重复的节模式足够解释了这些偏见.
- 研究结果提供了对决策中的习惯性选择倾向的见解.
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