Lee Jessica C, Lovibond Peter F, Hayes Brett K
University of New South Wales Sydney, Sydney, NSW, Australia.
Q J Exp Psychol (Hove). 2019 Nov;72(11):2647-2657. doi: 10.1177/1747021819857065. Epub 2019 Jun 21.
In property induction tasks, encountering a diverse range of instances (e.g., hippos and hamsters) with a given property usually increases our willingness to generalise that property to a novel instance, relative to non-diverse evidence (e.g., hippos and rhinos). Although generalisation in property induction and predictive learning tasks share conceptual similarities, it is unknown whether this diversity principle applies to generalisation of a predictive association. We tested this hypothesis in two predictive learning experiments using differential training where one category of stimuli (e.g., fruits) predicted an outcome and another category (e.g., vegetables) predicted no outcome. We compared generalisation between a Non-Diverse group who were presented with non-diverse evidence in both positive (predicted the outcome) and negative (predicted no outcome) categories, and two groups who received the same training as the Non-Diverse group but with a more diverse range of exemplars in the positive (Diverse+ group) or negative (Diverse- group) category. Diversity effects were found for both positive and negative categories, in that learning about a diverse range of exemplars increased generalisation of a predictive association to novel exemplars from that same category. The results suggest that diversity, a key principle describing how we reason inductively, also applies to generalisation in associative learning tasks.
在属性归纳任务中，相对于非多样化证据（如河马和犀牛），遇到具有给定属性的各种不同实例（如水牛和仓鼠）通常会增加我们将该属性推广到新实例的意愿。尽管属性归纳中的推广和预测性学习任务有概念上的相似之处，但尚不清楚这种多样性原则是否适用于预测性关联的推广。我们在两个预测性学习实验中检验了这一假设，实验采用差异训练，其中一类刺激（如水果）预测一个结果，另一类（如蔬菜）不预测结果。我们比较了一个非多样化组（在正性（预测结果）和负性（不预测结果）类别中都呈现非多样化证据）与另外两组的推广情况，另外两组接受与非多样化组相同的训练，但在正性（多样化+组）或负性（多样化-组）类别中有更多样化的示例。在正性和负性类别中都发现了多样性效应，即了解各种各样的示例会增加预测性关联向同一类别新示例的推广。结果表明，多样性作为描述我们归纳推理方式的一个关键原则，也适用于联想学习任务中的推广。
