Can You Imagine... A Language for Combinatorial Creativity?

  • Fabian M. SuchanekEmail author
  • Colette Menard
  • Meghyn Bienvenu
  • Cyril Chapellier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9981)


Combinatorial creativity combines existing concepts in a novel way in order to produce new concepts. For example, we can imagine jewelry that measures blood pressure. For this, we would combine the concept of jewelry with the capabilities of medical devices. In this paper, we concentrate on creating new concepts in the description logic \({\mathcal {EL}}\). We propose a novel language to this effect, and study its properties and complexity. We show that our language can be used to model existing inventions and (to a limited degree) to generate new concepts.


Normal Form Description Logic Original Concept Target Concept Concept Definition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was partially supported by Labex DigiCosme (project ANR-11-LABEX-0045-DIGICOSME) operated by ANR as part of the program “Investissement d’Avenir” Idex Paris-Saclay (ANR-11-IDEX-0003-02).


  1. 1.
    Goguen, J.A., Harrell, D.F.: Style: a computational and conceptual blending-based approach. In: Argamon, S., Burns, K., Dubnov, S. (eds.) The Structure of Style. Springer, Heidelberg (2010)Google Scholar
  2. 2.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  3. 3.
    Baader, F., Küsters, R., Molitor, R.: Computing least common subsumers in description logics with existential restrictions. In: IJCAI (1999)Google Scholar
  4. 4.
    Besold, T.R., Plaza, E.: Generalize, blend: concept blending based on generalization, analogy, and amalgams. In: ICCC (2015)Google Scholar
  5. 5.
    Boden, M.A., Mind, T.C.: Myths and Mechanisms. Routledge, Abingdon-on-Thames (2004)Google Scholar
  6. 6.
    Confalonieri, R., Schorlemmer, M., Plaza, E., Eppe, M., Kutz, O., Peñaloza, R.: Upward refinement for conceptual blending in description logic: an ASP-based approach and case study in EL++. In: Joint Ontology Workshops (2015)Google Scholar
  7. 7.
    Falkenhainer, B., Forbus, K.D., Gentner, D.: The structure-mapping engine: algorithm and examples. Artif. Intell. 41, 1–63 (1989)CrossRefzbMATHGoogle Scholar
  8. 8.
    Fauconnier, G., Turner, M.: Conceptual integration networks. Cogn. Sci. 22(2), 133–187 (1998)CrossRefGoogle Scholar
  9. 9.
    Ferré, S., Rudolph, S.: Advocatus diaboli - exploratory enrichment of ontologies with negative constraints. In: EKAW (2012)Google Scholar
  10. 10.
    Giacomo, G.D., Lenzerini, M., Poggi, A., Rosati, R.: On the update of description logic ontologies at the instance level. In: AAAI (2006)Google Scholar
  11. 11.
    Goguen, J.: What is a concept? In: Dau, F., Mugnier, M.-L., Stumme, G. (eds.) ICCS 2005. LNCS (LNAI), vol. 3596, pp. 52–77. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  12. 12.
    Hatchuel, A., Weil, B.: C-K design theory: an advanced formulation. Res. Eng. Des. 19(4), 181 (2009)CrossRefGoogle Scholar
  13. 13.
    Konev, B., Ludwig, M., Walther, D., Wolter, F.: The logical difference for the lightweight description logic EL. CoRR, abs/1401.5850 (2014)Google Scholar
  14. 14.
    Kutz, O., Bateman, J., Neuhaus, F., Mossakowski, T., Bhatt, M.: Computational Creativity Research: Towards Creative Machines. Springer, Heidelberg (2015). E Pluribus UnumGoogle Scholar
  15. 15.
    Liu, H., Singh, P.: Conceptnet. BT Technol. J. 22(4), 211–226 (2004)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Llano, M., Hepworth, R., Colton, S., Charnley, J., Gow, J.: Automating fictional ideation using conceptnet. In: AISB14 Symposium on Computational Creativity (2014)Google Scholar
  17. 17.
    Noia, T.D., Sciascio, E.D., Donini, F.M.: Semantic matchmaking as non-monotonic reasoning: a description logic approach. Artif. Int. Res. 29, 269–307 (2007)zbMATHGoogle Scholar
  18. 18.
    Qi, G., Yang, F.: A survey of revision approaches in description logics. In: Web Reasoning and Rule Systems (2008)Google Scholar
  19. 19.
    Ritchie, G.: Some empirical criteria for attributing creativity to a computer program. Minds Mach. 17(1), 67–99 (2007)CrossRefGoogle Scholar
  20. 20.
    Schmidt, M., Krumnack, U., Gust, H., Kühnberger, K.-U.: Heuristic-driven theory projection: an overview. In: Prade, H., Richard, G. (eds.) Computational Approaches to Analogical Reasoning: Current Trends. Springer, Heidelberg (2014)Google Scholar
  21. 21.
    Schorlemmer, M., Smaill, A., Kühnberger, K.-U., Kutz, O., Colton, S., Cambouropoulos, E., Pease, A.: Coinvent: towards a computational concept invention theory. In ICCC (2014)Google Scholar
  22. 22.
    Suchanek, F.M., Menard, C., Bienvenu, M., Chapellier, C.: A language for combinatorial creativity. Technical report, Telecom ParisTech (2016).
  23. 23.
    Teege, G.: Making the difference: a subtraction operation for DL. In: KR (1994)Google Scholar
  24. 24.
    Thagard, P., Stewart, T.C.: The AHA! experience: creativity through emergent binding in neural networks. Cogn. Sci. 35(1), 1–33 (2011)CrossRefGoogle Scholar
  25. 25.
    Toivonen, H., Colton, S., Cook, M., Ventura, D. (eds). International Conference on Computational Creativity (2015)Google Scholar
  26. 26.
    Veale, T., O’Donoghue, D., Keane, M.T.: Computation and blending. Cogn. Ling. 11(3/4), 253–281 (2000)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Fabian M. Suchanek
    • 1
    Email author
  • Colette Menard
    • 2
  • Meghyn Bienvenu
    • 3
  • Cyril Chapellier
    • 1
  1. 1.Télécom ParisTechParisFrance
  2. 2.STIMParisFrance
  3. 3.LIRMM MontpellierParisFrance

Personalised recommendations