Blending under deconstruction
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Blending under deconstruction The roles of logic, ontology, and cognition in computational concept invention Roberto Confalonieri1,2
· Oliver Kutz1
© The Author(s) 2019
Abstract The cognitive-linguistic theory of conceptual blending was introduced by Fauconnier and Turner in the late 90s to provide a descriptive model and foundational approach for the (almost uniquely) human ability to invent new concepts. Whilst blending is often described as ‘fluid’ and ‘effortless’ when ascribed to humans, it becomes a highly complex, multiparadigm problem in Artificial Intelligence. This paper aims at presenting a coherent computational narrative, focusing on how one may derive a formal reconstruction of conceptual blending from a deconstruction of the human ability of concept invention into some of its core components. It thus focuses on presenting the key facets that a computational framework for concept invention should possess. A central theme in our narrative is the notion of refinement, understood as ways of specialising or generalising concepts, an idea that can be seen as providing conceptual uniformity to a number of theoretical constructs as well as implementation efforts underlying computational versions of conceptual blending. Particular elements underlying our reconstruction effort include ontologies and ontology-based reasoning, image schema theory, spatio-temporal reasoning, abstract specification, social choice theory, and axiom pinpointing. We overview and analyse adopted solutions and then focus on open perspectives that address two core problems in computational approaches to conceptual blending: searching for the shared semantic structure between concepts—the socalled generic space in conceptual blending—and concept evaluation, i.e., to determine the value of newly found blends. Keywords Computational concept invention · Conceptual blending · Ontologies · Image schemas · Refinement operators Roberto Confalonieri
[email protected] Oliver Kutz [email protected] 1
Faculty of Computer Science, Free University of Bozen-Bolzano, Piazza Domenicani - Domenikanerplatz, 3, 39100 Bozen-Bolzano, Italy
2
Present address: Telef´onica Innovaci´on Alpha, Plac¸a d’Ernest Lluch i Martin, 5, E-08019 Barcelona, Spain
R. Confalonieri, O. Kutz
Mathematics Subject Classification (2010) 97R40 · 68T27
1 Introduction How do you take a piece of raw fish, spaghetti, and some herbs, and turn it into a dish? How should you fill that empty canvas with colour? What makes a piano an instrument to play music on, and not a tool for cooking? What makes a question a part of a scientific inquiry? These, and many similar questions, have to do with the imaginative mind of humans, their ability to invent new concepts, and more broadly, the human potential for creativity. Computational creativity is a multidisciplinary endeavour. Although the field started as part of research in Artificial Intelligence, it more recently also strongly overlaps and interacts with topics in cognitive linguistics and psychology, philosophy and
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