当前位置: X-MOL 学术Ann. Math. Artif. Intel. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Towards a model of creative understanding: deconstructing and recreating conceptual blends using image schemas and qualitative spatial descriptors
Annals of Mathematics and Artificial Intelligence ( IF 1.2 ) Pub Date : 2019-02-14 , DOI: 10.1007/s10472-019-09619-9
Zoe Falomir , Enric Plaza

Computational models of novel concept understanding and creativity are addressed in this paper from the viewpoint of conceptual blending theory (CBT). In our approach, a novel, unknown concept is addressed in a communication setting, where this novel concept, created as a blend by an emitter agent, sends a communicative object (words, or in this paper, a visual representation of that concept) to another agent. When received by a computational agent, a novel concept for that communicative object can only be understood by blending concepts already known by that agent. In this paper, we first posit that understanding new concepts via blending is also a creative process. Albeit different from generating conceptual blends, understanding a novel concept via blending involves the disintegration and decompression of that novel concept, in such a way that the receiver of that concept is able to re-create the conceptual network supposedly intended by the emitter of the novel concept. Secondly, we also propose image schemas as a tool that agents can use to interpret the spatial information obtained when disintegrating/unpacking novel concepts and then re-create the new blend. This process is studied in a communication setting where semiotics and meaning are conveyed by visual and spatial signs (instead of the usual setting of natural language or text). In this case study, qualitative spatial descriptors are applied for obtaining a formal description of an icon or pictogram, which is later assigned a meaning by a process of conceptual blending using image schemas.

中文翻译:

迈向创造性理解模型:使用图像模式和定性空间描述符解构和重新创建概念混合

本文从概念混合理论 (CBT) 的角度讨论了新概念理解和创造力的计算模型。在我们的方法中,一个新的、未知的概念在通信环境中得到解决,这个新概念由发射器代理创建为混合,将一个通信对象(单词,或在本文中,该概念的视觉表示)发送到另一个代理。当被计算代理接收时,该通信对象的新概念只能通过混合该代理已知的概念来理解。在本文中,我们首先假设通过混合理解新概念也是一个创造性的过程。尽管与生成概念混合不同,通过混合理解一个新概念涉及到该新概念的分解和解压,以这样一种方式,该概念的接收者能够重新创建新概念的发射者所期望的概念网络。其次,我们还提出了图像模式作为一种工具,代理可以使用它来解释在分解/解包新概念时获得的空间信息,然后重新创建新的混合。这个过程是在交流环境中研究的,其中符号学和意义通过视觉和空间符号(而不是自然语言或文本的通常环境)传达。在本案例研究中,定性空间描述符用于获得图标或象形图的正式描述,稍后通过使用图像模式的概念混合过程为其分配含义。
更新日期:2019-02-14
down
wechat
bug