Adaptive learning and risk taking
Adaptive learning and risk taking
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DOI：
10.1037/0033-295x.114.1.177
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发表时间：
2007-01-01
影响因子：
5.4
通讯作者：
Denrell, Jerker
中科院分区：
文献类型：
--
作者：
Denrell, Jerker
人类和动物从经验中学习，减少抽样的概率与过去的结果差的替代品。通过模拟，J.G. March（1996）说明了这种适应性抽样如何导致风险规避和风险寻求行为。在这篇文章中，作者发展了一个正式的理论，如何适应性抽样影响风险承担。他表明，一个风险中性的决策者可能会学习更喜欢一个确定的事情，而不是一个不确定的替代品，具有相同的期望值和对称分布，即使决策者遵循最优的学习策略。如果不确定性选择的分布是负偏态的，风险寻求行为就会出现。与最近的实验一致，该模型暗示，有关放弃收益的信息会增加冒险行为。
Humans and animals learn from experience by reducing the probability of sampling alternatives with poor past outcomes. Using simulations, J. G. March (1996) illustrated how such adaptive sampling could lead to risk-averse as well as risk-seeking behavior. In this article, the author develops a formal theory of how adaptive sampling influences risk taking. He shows that a risk-neutral decision maker may learn to prefer a sure thing to an uncertain alternative with identical expected value and a symmetric distribution, even if the decision maker follows an optimal policy of learning. If the distribution of the uncertain alternative is negatively skewed, risk-seeking behavior can emerge. Consistent with recent experiments, the model implies that information about foregone payoffs increases risk taking.