Abstract Category-based induction is an inferential mechanism that uses knowledge of conceptual relations in order to estimate how likely is for a property to be projected from one category to another. During the last decades, psychologists have identified several features of this mechanism, and they have proposed different formal models of it. In this article; we propose a new mathematical model for category-based induction based on distances on conceptual spaces. We show how this model can predict most of the properties of this kind of reasoning while providing a solid theoretical foundation for it. We also show that it subsumes some of the previous models proposed in the literature and that it generates new predictions.

中文翻译：

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概念空间中基于类别的归纳

摘要 基于类别的归纳是一种推理机制，它使用概念关系的知识来估计属性从一个类别投射到另一个类别的可能性。在过去的几十年里，心理学家已经确定了这种机制的几个特征，并提出了不同的正式模型。在本文中; 我们提出了一种基于概念空间距离的基于类别归纳的新数学模型。我们展示了该模型如何预测这种推理的大部分属性，同时为其提供坚实的理论基础。我们还表明，它包含了文献中提出的一些先前模型，并生成了新的预测。