A Choice Prediction Competition: Choices from Experience and from Description
A Choice Prediction Competition: Choices from Experience and from Description
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DOI：
10.1002/bdm.683
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发表时间：
2010-01-01
影响因子：
2
通讯作者：
Lebiere, Christian
中科院分区：
文献类型：
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作者：
Erev, Ido;Ert, Eyal;Lebiere, Christian
Erev，Ert和Roth组织了三次选择预测比赛，专注于三个相关的选择任务：根据描述的一次性决策（风险下的决策），根据经验的一次性决策和根据经验的重复决策。每个竞赛都基于两个实验数据集：估计数据集和竞赛数据集。生成这两个数据集的研究使用相同的方法和受试者池，并检查从相同分布中随机选择的决策问题。在收集了用于估计的实验数据后，组织者将这些数据以及它们与几个基线模型的拟合情况发布在网络上，并邀请其他研究人员竞争预测第二组（竞争）实验会话的结果。14个团队回应了挑战：本文的最后7位作者是获胜团队的成员。结果突出的鲁棒性之间的差异，从描述和决策的经验。最好的预测决策的描述得到了随机变量的前景理论假设的加权值的敏感性随着累积支付函数之间的距离。从经验中获得的决策的最佳预测模型，假设依赖于小样本。竞争方法的优点和局限性进行了讨论。版权所有（C）2009约翰威利父子有限公司
Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: One shot decisions from description (decisions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets: An estimation dataset, and a competition dataset. The studies that generated the two datasets used the same methods and subject pool, and examined decision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the second (competition) set of experimental sessions. Fourteen teams responded to the challenge: The last seven authors of this paper are members of the winning teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the sensitivity to the weighted values decreases with the distance between the cumulative payoff functions. The best predictions of decisions from experience were obtained with models that assume reliance on small samples. Merits and limitations of the competition method are discussed. Copyright (C) 2009 John Wiley & Sons, Ltd.