Abstract

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.

Publication Type:	Article
Additional Information:	This is an Accepted Manuscript of an article published by Taylor & Francis in 'Connection Science' on 02 Nov 2017, available online: http://www.tandfonline.com/10.1080/09540091.2017.1326463.
Publisher Keywords:	Concept blending, cognitive artificial intelligence, computational creativity, analogy, amalgams
Departments:	School of Science & Technology > Computer Science

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