基于常规的学习对决策的影响

T. Brenner
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引用次数: 6

摘要

经济学文献中提出了各种数学模型来对有界理性学习进行建模。这些模型中的每一个都考虑了一种学习类型,比如模仿、坐式学习、试错或强化学习。本文结合了几种有界理性学习的类型,提出了一种更通用的学习模型。然后,在涉及风险的相当一般的决策情况下检查该学习模型的特征。研究了在何种条件下学习导致预期效用最大化行为。在此基础上,分析了学习的不同方面会对效用最大化行为产生什么样的偏差。论述代码。C44 D83。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implications of routine-based learning for decision making
Various mathematical models have been proposed in the economic literature for the modelling of boundedly rational learning. Each of these models considers one type of learning, like imitation, sat- iscing, trial-and-error or reinforcement learning. This paper combines several types of boundedly rational learning and develops a more gen- eral learning model. Then, the characteristics of this learning model are examined for a quite general decision situation involving risk. It is studied under which conditions learning leads to an expected utility maximising behaviour. Furthermore, it is analysed what kind of devia- tions from the utility maximising behaviour are caused by the dierent aspects of learning. Classication Codes. C44, D83.
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