Towards a computational- and algorithmic-level account of concept blending using analogies and amalgams

Concept blending – a cognitive process which allows for the combination of certain elements (and their relations) from originally distinct conceptual spaces into a new unified space combining these previously separate elements, and enables reasoning and inference over the combination – is taken as a...

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Bibliographic Details
Main Authors: Tarek R. Besold, Kai-Uwe Kühnberger, Enric Plaza
Format: Article
Language:English
Published: Taylor & Francis Group 2017-10-01
Series:Connection Science
Subjects:
Online Access:http://dx.doi.org/10.1080/09540091.2017.1326463
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Summary:Concept blending – a cognitive process which allows for the combination of certain elements (and their relations) from originally distinct conceptual spaces into a new unified space combining these previously separate elements, and enables reasoning and inference over the combination – is taken as a key element of creative thought and combinatorial creativity. In this article, we summarise our work towards the development of a computational-level and algorithmic-level account of concept blending, combining approaches from computational analogy-making and case-based reasoning (CBR). We present the theoretical background, as well as an algorithmic proposal integrating higher-order anti-unification matching and generalisation from analogy with amalgams from CBR. The feasibility of the approach is then exemplified in two case studies.
ISSN:0954-0091
1360-0494