Adult Regularization of Inconsistent Input Depends on Pragmatic Factors
Adult Regularization of Inconsistent Input Depends on Pragmatic Factors
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DOI：
10.1080/15475441.2015.1052449
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发表时间：
2016-01-01
影响因子：
1.5
通讯作者：
Perfors, Amy
中科院分区：
文献类型：
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作者：
Perfors, Amy
在各种领域中，接受仅部分一致的输入的成年人不会丢弃不一致的部分（正则化），而是维持其行为中一致和不一致部分的概率（概率匹配）。这项研究调查了成年人概率匹配的可能性，至少部分是因为他们对学习问题提出了两个务实的假设：（a）他们看到的变化是可预测的而不是随机的；（b）他们的目标是正确学习这种变化。两个实验的证据表明，当消除任何一个假设时，人们的概率匹配会减少，因此正则化程度会更高。这些结果是根据正则化中的年龄和领域差异进行讨论的。
In a variety of domains, adults who are given input that is only partially consistent do not discard the inconsistent portion (regularize) but rather maintain the probability of consistent and inconsistent portions in their behavior (probability match). This research investigates the possibility that adults probability match, at least in part, because of two pragmatic assumptions they bring to the learning problem: (a) that the variation they see is predictable rather than random and (b) that their goal is to correctly learn that variation. Evidence from two experiments demonstrates that when either assumption is eliminated, people probability match less and therefore regularize more. These results are discussed with respect to age and domain differences in regularization.