The cognitive-linguistic theory of conceptual blending was introduced by Fauconnier and Turner in the late 90s to provide a descriptive model and foundational approach for the (almost uniquely) human ability to invent new concepts. Whilst blending is often described as ‘fluid’ and ‘effortless’ when ascribed to humans, it becomes a highly complex, multi-paradigm problem in Artificial Intelligence. This paper aims at presenting a coherent computational narrative, focusing on how one may derive a formal reconstruction of conceptual blending from a deconstruction of the human ability of concept invention into some of its core components. It thus focuses on presenting the key facets that a computational framework for concept invention should possess. A central theme in our narrative is the notion of refinement, understood as ways of specialising or generalising concepts, an idea that can be seen as providing conceptual uniformity to a number of theoretical constructs as well as implementation efforts underlying computational versions of conceptual blending. Particular elements underlying our reconstruction effort include ontologies and ontology-based reasoning, image schema theory, spatio-temporal reasoning, abstract specification, social choice theory, and axiom pinpointing. We overview and analyse adopted solutions and then focus on open perspectives that address two core problems in computational approaches to conceptual blending: searching for the shared semantic structure between concepts—the so-called generic space in conceptual blending—and concept evaluation, i.e., to determine the value of newly found blends.

中文翻译：

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解构下的融合

Fauconnier 和 Turner 在 90 年代后期引入了概念混合的认知语言学理论，为（几乎独一无二的）人类发明新概念的能力提供了描述性模型和基础方法。虽然混合通常被描述为人类的“流畅”和“轻松”，但它成为人工智能中一个高度复杂的多范式问题。本文旨在呈现一种连贯的计算叙述，重点关注如何从概念发明的人类能力解构到其某些核心组件中，推导出概念融合的形式重构。因此，它侧重于介绍概念发明的计算框架应具备的关键方面。我们叙述的一个中心主题是精致的概念，被理解为专门化或概括概念的方式，这种想法可以被视为为许多理论构造以及概念混合的计算版本的实现工作提供概念一致性。我们重建工作背后的特定元素包括本体论和基于本体论的推理、图像模式理论、时空推理、抽象规范、社会选择理论和公理精确定位。我们概述和分析采用的解决方案，然后专注于解决概念混合计算方法中的两个核心问题的开放视角：搜索概念之间的共享语义结构——所谓的概念混合中的通用空间——和概念评估，即确定新发现的混合物的价值。一个可以被视为为许多理论结构以及概念混合的计算版本的实现工作提供概念一致性的想法。我们重建工作背后的特定元素包括本体论和基于本体论的推理、图像模式理论、时空推理、抽象规范、社会选择理论和公理精确定位。我们概述和分析采用的解决方案，然后专注于解决概念混合计算方法中的两个核心问题的开放视角：搜索概念之间的共享语义结构——所谓的概念混合中的通用空间——和概念评估，即确定新发现的混合物的价值。一个可以被视为为许多理论结构以及概念混合的计算版本的实现工作提供概念一致性的想法。我们重建工作背后的特定元素包括本体论和基于本体论的推理、图像模式理论、时空推理、抽象规范、社会选择理论和公理精确定位。我们概述和分析采用的解决方案，然后专注于解决概念混合计算方法中的两个核心问题的开放视角：搜索概念之间的共享语义结构——所谓的概念混合中的通用空间——和概念评估，即确定新发现的混合物的价值。