2024-03-29T08:15:22Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1613392020-12-10T11:44:53Zcom_10261_60com_10261_4col_10261_313
A computational framework for conceptual blending
Eppe, Manfred
Maclean, Ewen
Confalonieri, Roberto
Kutz, Oliver
Schorlemmer, Marco
Plaza, Enric
Kühnberger, Kai-Uwe
Libera Università di Bolzano
German Academic Exchange Service
European Commission
Conceptual blending
Computational creativity
Cognitive science
Answer set programming
We present a computational framework for conceptual blending, a concept invention method that is advocated in cognitive science as a fundamental and uniquely human engine for creative thinking. Our framework treats a crucial part of the blending process, namely the generalisation of input concepts, as a search problem that is solved by means of modern answer set programming methods to find commonalities among input concepts. We also address the problem of pruning the space of possible blends by introducing metrics that capture most of the so-called optimality principles, described in the cognitive science literature as guidelines to produce meaningful and serendipitous blends. As a proof of concept, we demonstrate how our system invents novel concepts and theories in domains where creativity is crucial, namely mathematics and music. © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
We thank the reviewers for their valuable and constructive comments and feedback. We also thank Mihai Codescu, Free University of Bozen-Bolzano, Italy, for his support with HETS, as well as Maximos Kaliakatsos and Emilios Cambouropoulos, Aristotle University of Thessaloniki, Greece, for their valuable ideas and help with the music examples. The research presented in this article was partially supported by the COINVENT project (FET-Open grant number: 611553). Manfred Eppe received support by the German Academic Exchange Service (DAAD) as participant in the FITweltweit programme. Oliver Kutz and Roberto Confalonieri were supported by the unibz CRC project COCO “Computational Technologies for Concept Invention”. The authors thank the Department of Innovation, Research and University of the Autonomous Province of Bozen/Bolzano for covering the Open Access publication costs.
Peer Reviewed
2018-02-26T16:25:18Z
2018-02-26T16:25:18Z
2018
2018-02-26T16:25:19Z
artículo
http://purl.org/coar/resource_type/c_6501
doi: 10.1016/j.artint.2017.11.005
issn: 0004-3702
Artificial Intelligence 256: 105- 129 (2018)
http://hdl.handle.net/10261/161339
10.1016/j.artint.2017.11.005
http://dx.doi.org/10.13039/501100001655
http://dx.doi.org/10.13039/501100000780
Publisher's version
Sí
open
Elsevier