Towards a model of creative understanding: deconstructing and recreating conceptual blends using image schemas and qualitative spatial descriptors

  • Zoe Falomir
  • Enric PlazaEmail author


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.


Computational creativity Concept blending Qualitative spatial descriptors Image schemas Concept understanding Novel concepts 

Mathematics Subject Classification 2010



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This research has been partially supported by Cognitive Qualitative Descriptions and Applications (CogQDA) of the Central Research Development Fund (CRDF) at University of Bremen through the 04-Independent Projects for Postdocs action and project DIVERSIS (CSIC Intramural 201750E064).


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Bremen Spatial Cognition Centre (BSCC)University of BremenBremenGermany
  2. 2.IIIA, Artificial Intelligence Research Institute CSICSpanish Council for Scientific ResearchCataloniaSpain

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