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How Category Selection Impacts Inference Reliability: Inheritance Inference From an Ecological Perspective
Cognitive Science ( IF 2.617 ) Pub Date : 2021-04-20 , DOI: 10.1111/cogs.12971
Paul D Thorn 1 , Gerhard Schurz 1
Affiliation  

This article presents results from a simulation‐based study of inheritance inference, that is, inference from the typicality of a property among a “base” class to its typicality among a subclass of the class. The study aims to ascertain which kinds of inheritance inferences are reliable, with attention to the dependence of their reliability upon the type of environment in which inferences are made. For example, the study addresses whether inheritance inference is reliable in the case of “exceptional subclasses” (i.e., subclasses that are known to be atypical in some respect) and attends to variations in reliability that result from variations in the entropy level of the environment. A further goal of the study is to show that the reliability of inheritance inference depends crucially on which sorts of base classes are used in making inferences. One approach to inheritance inference treats the extension of any atomic predicate as a suitable base class. A second approach identifies suitable base classes with the cells of a partition (of a preselected size k) of the domain of objects that satisfies the condition of maximizing the similarity of objects that are assigned to the same class. In addition to permitting more inferences, our study shows that the second approach results in inheritance inferences that are far more reliable, particularly in the case of exceptional subclasses.

中文翻译:

类别选择如何影响推理可靠性:从生态学角度的继承推理

本文介绍了基于模拟的继承推断研究的结果,即从“基”类中的属性的典型性到该类的子类中的典型性的推断。该研究旨在确定哪种继承推断是可靠的,并注意它们的可靠性对进行推断的环境类型的依赖性。例如,该研究解决了在“异常子类”(即已知在某些方面不典型的子类)的情况下继承推断是否可靠,并关注由环境熵水平变化引起的可靠性变化. 该研究的另一个目标是表明继承推断的可靠性在很大程度上取决于在进行推断时使用了哪种基类。任何原子谓词作为合适的基类。第二种方法使用满足最大化分配给同一类的对象的相似性的条件的对象域的分区(具有预选大小k)的单元来识别合适的基类。除了允许更多的推断之外,我们的研究表明,第二种方法导致的继承推断更加可靠,特别是在特殊子类的情况下。
更新日期:2021-04-21
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