Department of Humanities and Social Sciences, Rose-Hulman Institute of Technology, United States.
School of Informatics, The University of Edinburgh, United Kingdom.
Cognition. 2017 Nov;168:46-64. doi: 10.1016/j.cognition.2017.06.017. Epub 2017 Jun 26.
People are capable of learning other people's preferences by observing the choices they make. We propose that this learning relies on inverse decision-making-inverting a decision-making model to infer the preferences that led to an observed choice. In Experiment 1, participants observed 47 choices made by others and ranked them by how strongly each choice suggested that the decision maker had a preference for a specific item. An inverse decision-making model generated predictions that were in accordance with participants' inferences. Experiment 2 replicated and extended a previous study by Newtson (1974) in which participants observed pairs of choices and made judgments about which choice provided stronger evidence for a preference. Inverse decision-making again predicted the results, including a result that previous accounts could not explain. Experiment 3 used the same method as Experiment 2 and found that participants did not expect decision makers to be perfect utility-maximizers.
人们可以通过观察他人的选择来学习他人的偏好。我们提出，这种学习依赖于反向决策——反转决策模型以推断导致观察到的选择的偏好。在实验 1 中，参与者观察了 47 次他人的选择，并根据每个选择对决策者对特定项目的偏好的强烈程度对其进行了排序。反向决策模型生成的预测与参与者的推断一致。实验 2 复制并扩展了 Newtson（1974）的先前研究，其中参与者观察了一对选择并对哪个选择提供了更强的偏好证据进行了判断。反向决策再次预测了结果，包括之前的解释无法解释的结果。实验 3 使用与实验 2 相同的方法，发现参与者并不期望决策者是完美的效用最大化者。
