Confalonieri, RobertoRobertoConfalonieriEppe, ManfredManfredEppeSchorlemmer, MarcoMarcoSchorlemmerKutz, OliverOliverKutzPeñaloza, RafaelRafaelPeñalozaPlaza, EnricEnricPlaza2022-04-252022-04-252018-03-01Annals of Mathematics and Artificial Intelligence 82 (1-3) : 69-99 (2018-03-01)http://hdl.handle.net/11420/12362Conceptual blending is a mental process that serves a variety of cognitive purposes, including human creativity. In this line of thinking, human creativity is modeled as a process that takes different mental spaces as input and combines them into a new mental space, called a blend. According to this form of combinational creativity, a blend is constructed by taking the commonalities among the input mental spaces into account, to form a so-called generic space, and by projecting the non-common structure of the input spaces in a selective way to the novel blended space. Since input spaces for interesting blends are often initially incompatible, a generalisation step is needed before they can be blended. In this paper, we apply this idea to blend input spaces specified in the description logic + + and propose an upward refinement operator for generalising + + concepts. We show how the generalisation operator is translated to Answer Set Programming (ASP) in order to implement a search process that finds possible generalisations of input concepts. The generalisations obtained by the ASP process are used in a conceptual blending algorithm that generates and evaluates possible combinations of blends. We exemplify our approach in the domain of computer icons.en1012-244320181-36999Answer set programmingComputational creativityConceptual blendingDescription logicJournal Article10.1007/s10472-016-9524-8Journal Article