Towards a computational framework for function-driven concept invention
| Autor(en): | Potyka, N. Gómez-Ramírez, D. Kühnberger, K.-U. |
Herausgeber: | Steunebrink, B. Wang, P. Goertzel, B. |
Stichwörter: | Blending; Patents and inventions, Blending theories; Computational framework; NP Complete; Optimal combination; Structural similarity, Computation theory | Erscheinungsdatum: | 2016 | Herausgeber: | Springer Verlag | Enthalten in: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Band: | 9782 | Startseite: | 212 | Seitenende: | 222 | Zusammenfassung: | We propose a novel framework for computational concept invention. As opposed to recent implementations of Fauconnier's and Turner's Conceptual Blending Theory, our framework simplifies computational concept invention by focusing on concepts' functions rather than on structural similarity of concept descriptions. Even though creating an optimal combination of concepts that achieves the desired functions is NP-complete in general, some interesting special cases are tractable. © Springer International Publishing Switzerland 2016. |
Beschreibung: | Conference of 9th International Conference on Artificial General Intelligence, AGI 2016 ; Conference Date: 16 July 2016 Through 19 July 2016; Conference Code:177049 |
ISBN: | 9783319416489 | ISSN: | 03029743 | DOI: | 10.1007/978-3-319-41649-6_21 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977595470&doi=10.1007%2f978-3-319-41649-6_21&partnerID=40&md5=7fc4b5f97f319efd1d469ed59f836fd5 |
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