Characterising cognitively useful blends: formalising governing principles of conceptual blending
We propose a model that conceptualises diagrammatic sensemaking and reasoning as blends of image schemas – patterns derived from our perceptual and embodied experiences and interactions with the environment – with the geometric structure of the diagram. Our ultimate goal is to develop an algorithmic...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión enviada para evaluación y publicación |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/377992 |
| Acceso en línea: | http://hdl.handle.net/10261/377992 |
| Access Level: | acceso abierto |
| Palabra clave: | Diagrammatic reasoning Sensemaking Image schema Conceptual blending Governing principles Category theory |
| Sumario: | We propose a model that conceptualises diagrammatic sensemaking and reasoning as blends of image schemas – patterns derived from our perceptual and embodied experiences and interactions with the environment – with the geometric structure of the diagram. Our ultimate goal is to develop an algorithmic method for determining several potential blends that hold cognitive value for observers. Building upon our formal, category-theoretic approach to conceptual blending, we extend it by formalising two governing principles of blending. These principles serve as guides for the blending process, directing the cognitive construction of the blend. As these principles may compete with each other and favour different blend structures, we argue that their combination leads to cognitively useful blends. Through examples of several alternative blends of the geometric configuration of a particular Hasse diagram with the SCALE image schema, we demonstrate the implications of these competing pressures on diagrammatic reasoning. Consequently, this work disambiguates and operationalises the intricacies of conceptual blending, advancing its applicability in computational systems. |
|---|